Auto-claude-code-research-in-sleep

📰 ARIS-Code v0.4.28 (2026-09) — latest: ARIS_REASONING_EFFORT works on the Anthropic channel (#446), tool calls through relays that send a {} placeholder no longer fail (#444), and the OS proxy on Windows / macOS is used without exporting HTTPS_PROXY (#401). v0.4.27: launching and quitting the REPL no longer leaves an empty session file, and /resume lists only sessions with messages (#439 follow-up). v0.4.26 made Fable 5.1 the fable alias and the first /model entry (the default executor stays Opus 5). v0.4.25 is the reviewer-bridge release: codex-cli 0.154 removed codex mcp-server, so every Codex review from ARIS-Code died on an updated codex. The reviewer now runs over a built-in codex exec bridge — no mcpServers.codex entry, old entries migrate in memory, thread records interoperate with ARIS's Python bridge. Also: /since replays everything after your last input (folded like the live display, /since full for complete output), /resume lists sessions with indices and shows where you stopped (#439), Windows multi-line paste no longer submits line by line (#430, pending confirmation), the Windows shim message carries the native installer (#428), and the bundle moves to 83 skills on GPT-6-Astra. Recent headliners: v0.4.24 — Claude 5 model refresh (Opus 5 default, Fable 5 tier, availability chain) and v0.4.23 — output folding. Caps a 24-release run (v0.4.5 → v0.4.28); per-release detail below. Credits: @GetIT-Sunday, @Anduin9527, @GO-player-hhy, @Jxy-yxJ, @screw-44, @StevenUST, @opposj, @ShijunLei-cn, @algojogacor, @YukinoshitaLove, @jinliye-2026, @SajimJC, @JasmineLCY.

Per-release details (v0.4.5 → v0.4.28)

v0.4.28 (2026-09-28) — ARIS_REASONING_EFFORT now works on the Anthropic channel (#446): low / medium / high / xhigh / max for the main session and subagents; unset, requests are unchanged. ARIS_MAX_TOKENS raises the output cap when a high effort runs into it. autoCompactEnabled: false in settings turns automatic compaction off. 🐛 #444 tool calls through relays that send a {} placeholder no longer fail with invalid tool input JSON. 🌐 System proxy on Windows / macOS is used without exporting HTTPS_PROXY (#401, by @JasmineLCY); NO_PROXY=* connects directly as before. Upgrading: if you already export ARIS_REASONING_EFFORT, have an OS proxy, or have autoCompactEnabled: false in settings, read the upgrade notes.

v0.4.27 (2026-09-19) — launching and quitting the REPL no longer leaves an empty session file; /resume lists only sessions with messages (#439 follow-up).

v0.4.26 (2026-09-16) — Fable 5.1: the fable alias now resolves to claude-fable-5-1, /model lists Fable 5.1 first (Fable 5 stays selectable) and the system-prompt identity names it; the default executor remains claude-opus-5 (the Mythos tier is $10/$50 vs Opus 5's $5/$25, so the default does not move). Saved executor_model values are ids, not aliases, and are untouched. Pricing already matched on fable; a test pins 5.1. Tests unchanged (aris-cli 225 + 4 e2e / runtime 252 / tools 71 / commands 6). Codex MCP (gpt-6-astra xhigh) gate: GO.

v0.4.25 (2026-09-16) — the reviewer-bridge release. codex-cli 0.154 removed codex mcp-server, the entry point ARIS-Code's aris setup had written into settings.json for every Codex review; on an updated codex every review call died. Built-in codex exec bridge: mcp__codex__codex / codex-reply run as codex exec --json with nothing to register — no settings entry, a legacy codex mcp-server entry is migrated in memory (env, -c defaults, requestTimeoutSecs, trust kept), an explicit Python-bridge entry is used as configured, thread records share ~/.codex/state/codex-exec/threads/ with the Python bridge, 1800 s budget for ultra audits, ARIS_CODEX_BRIDGE=0 restores the old path; aris doctor prints the effective backend. Found on the way: the model never received a Codex result's threadId (it lives only in structuredContent), so codex-reply could not continue a thread — results now start with a threadId: line. /since [full] replays the user's last input and everything after it with the live formatters (display only; after /resume and in --resume batch mode too); a dim hint after turns with ≥ 8 tool calls (ARIS_TURN_SUMMARY=0). #430 Windows consoles deliver no paste event, so each pasted line became its own Enter — lines are now merged into the input and never auto-submitted, Ctrl+C discards the rest (ARIS_PASTE_BURST=0; inferred from crossterm's source, pending confirmation on a Windows machine). #439 /resume lists sessions with [n] indices and ages and accepts an index, a unique id prefix or a path; the last turn is replayed after loading. #428 the .cmd-shim message carries the official native installer one-liner. Bundle 81→83 (pin 3e49e63 → 4734364): /proof-orchestrator, /research-implement-feature, 32 helpers (+review_gate.py, copilot_native_evidence.py, idea_discovery_gate.py), repo-root templates/ bundled; reviewer doctrine and system prompt on gpt-6-astra (fallback gpt-5.6-sol → gpt-5.5), explicit — reviewer: directives win, LlmReview results carry reviewer_model: so HTTP rounds report to review_gate.py truthfully; gpt-6-astra pricing tier $10/$50 (cache write $12.50, read $1). Tests: api 35+6 / aris-cli 225 + 4 e2e / runtime 252 / tools 71 / commands 6, all green; live codex exec fresh + resume roundtrip on codex-cli 0.154.0. Codex MCP (gpt-6-astra): ultra design gate (2 rounds), xhigh implementation gate per step (5/2/2/2 rounds), final whole-diff gate (2 rounds) → GO.

v0.4.24 (2026-08-09) — the Claude 5 model refresh (#392, requested by @YukinoshitaLove). Explicit --model claude-opus-5 / claude-fable-5 already passed through on every platform — this release makes them first-class. Default → claude-opus-5 (main session, subagents, aris setup; same $5/$25 tier as Opus 4.8); the v0.4.18 availability fallback becomes an ordered chain walk (Opus 5 → Opus 4.8 → Opus 4.7, one step per precise 404 not_found_error, explicit choices never silently change) — the naive constant swap would have stranded 4.7-only accounts and configs saved by v0.4.23's setup, a regression the cross-model review caught and an end-to-end mock-404 chain test now locks. /model picker adds Fable 5 / Opus 5 / Sonnet 5; new fable alias. New Mythos-class pricing tier (fable/mythos = $10/$50, cache write $12.50 / read $1, verified 2026-08 — previously fell to the conservative $15/$75 unknown-model tier, a 1.5× over-estimate); Opus 5 / Sonnet 5 pinned on their existing branches. Tests: api 41 / aris-cli 213 + 4 e2e / runtime 226 / tools 70 / commands 5, all green; live smoke on claude-opus-5, claude-fable-5 and the fable alias. Codex MCP (gpt-6-astra xhigh) implementation gate: NO-GO → NO-GO → GO.

v0.4.23 (2026-08-02) — the output-folding release (top real-user complaint: "aris dumps thinking and the full content of documents it reads onto the screen"). 🧹 Tool-output folding, display layer ONLY: the disk-verified culprits were format_read_result appending the ENTIRE read payload, bash pushing full stdout/stderr, grep dumping its full content blob, and the edit preview capping line counts but not line LENGTH. Now Read/Grep show the first 6 lines, Bash shows first 4 + last 4 per stream (stderr keeps its red), each kept line capped at 240 chars (the minified-single-line case), then one dim "… (+N more lines — set ARIS_TOOL_OUTPUT_LINES=0 for full output)" hint. ONE env knob: unset = defaults, a positive integer overrides every tool, 0 = the exact old display; the session, model context, --output-format json and /export are untouched and always complete. Thinking was verified to never print (Anthropic deltas only accumulate; Kimi reasoning_content only feeds the replay cache — the "thinking dump" perception came from the document dumps); two end-to-end sentinel tests (real binary vs mock SSE server) lock that thinking/reasoning never reaches the terminal. Interactive expand/collapse was deliberately rejected as over-engineering. 🐛 Bash timeout now kills the command: a timed-out call reported interrupted: true while the dropped tokio future left the child RUNNING — side effects landed after the report; now kill_on_drop (escape hatch ARIS_BASH_KILL_ON_TIMEOUT=0; background tasks untouched; locked by a real behavioral test — a timed-out "sleep 1 && touch marker" must not create the marker). 📦 Bundle 79→81 (pin 7182624 → 3e49e63): /integrity-forensics — the Anti-Autoresearch SHA-pinned thin launcher (span-anchored evidence ledger → GPT auditors propose → deterministic rules-only adjudicator decides → typed BLOCK/WARN gate + obligations ledger) — and /web-debug-search, +tools/forensics_gate.py (29 helpers, 104 embedded resources). 🎁 Also: grep's content mode no longer shows a false "0 matches" above real results (the gate caught that "numMatches": null serializes with the key present, defeating a naive presence check); all four crates' local-mock-server tests are now proxy-immune (a shell with http(s)_proxy set used to turn 15 tests red on a released tag — 127.0.0.1 was routed through the proxy). The rest of the runtime-state package (compaction re-arm, failed-turn cleanup, /cost dollars, SSE tail) ships as v0.4.24 — the cached-token cost fix is deliberately held back because it changes what the compaction trigger measures. Tests: api 41 / aris-cli 212 + 3 e2e / runtime 225 / tools 69 / commands 5 (+13), all green under a live proxy; new-code clippy delta zero. Codex MCP (gpt-6-astra): ultra scope+design adjudication, then a 3-round implementation gate (round 1 caught the null-serialization defeat and a non-hermetic behavioral test; round 3 GO).

v0.4.22 (2026-07-12) — the skills-resync + GPT-6-Astra release. 📦 Bundle resync (pin 7e3ab67 → 7182624, 93 commits): 79 bundled skills (+meta-apply, +paper-poster-html; paper-poster retired to a redirect stub), 28 tools helpers (8 new: capture_filter, evidence_check, iteration_log, provenance, run_state, threat_scan, meta_opt/trigger_eval + sample evals), 11 new shared-references docs (fan-out-pattern, acceptance-gate, external-cadence, skill-governance, compute-env-contract, resumable-runs, evidence-precheck, injection-hygiene, capture-antipatterns, output-composition, taste-calibration); sync hardening — ARIS_SYNC_EXPECT_SHA guard (aborts before touching assets if main moved; it caught a real move on first use) + exact-inventory drift tests + the vendored posterly MIT license text now ships. 🎛 GPT-6-Astra two-tier reviewer alignment: the CLI's system-prompt nudge now passes the skills' explicit model: gpt-6-astra + per-call effort pins through (the v0.4.17 blanket "never pass a model" rule would have silently stripped deep audits from ultra to xhigh), carries the canonical capability-only fallback chain (effort-unsupported → same model xhigh, deep tier only; model-unknown → explicit gpt-5.5+xhigh; never degrade on transport-class errors; an explicit call-level override disables the chain), pins approval-policy: "never" + explicit sandbox on every fresh codex call, and makes the HTTP fallback pre-dispatch-only with parameter stripping; the HTTP LlmReview default deliberately stays gpt-5.5 pending a real smoke; gpt-5.6 family pricing (sol $5/$30, terra $2.50/$15, luna $1/$6) verified against the official page; banner/Reviewer display//reviewer are honest about primary-vs-fallback (pure-Codex setups get status + guidance instead of a fake picker). 🐛 8 verified fixes: explicit --model was silently overridden by the saved executor model (model provenance now tracked end-to-end; the 4.8→4.7 availability fallback respects explicit choices; /model and /setup re-arm it); saved models no longer leak across provider transports (blank saved models count as absent; OpenAI transport with no model source fails fast; the first-run wizard's config now actually feeds startup model resolution); --output-format json never prompts (locked by a real end-to-end binary test against a mock SSE server); Windows aris login fixed (PKCE randomness read /dev/urandom → getrandom); Windows command probing fixed (the PowerShell tool probed itself through sh; now where.exe); codex .cmd shims classified honestly (three-state probe; setup requires explicit confirmation before writing a config the MCP client can't spawn); nested config.json warns instead of silently parsing to all-defaults; NotebookEdit mints collision-free cell ids. 🖥 New windows-latest CI job (workspace compile gate + three targeted test groups, each guarded against silent 0-test green). Tests: api 41 / aris-cli 204 + 1 e2e / runtime 223 / tools 69 / commands 5 (+54), all green; new-code clippy delta zero. Codex MCP (gpt-6-astra): ultra design gate — 5 rounds, NO-GO ×4 → GO — then a 3-round implementation gate whose round 2 caught a first-run config-wiring blocker before it shipped; 4 implementation subagents, every report disk-verified.

v0.4.21 (2026-06-28) — bug-fix patch: 5 new user-facing bugs from a Codex adversarial hunt (all disk-verified, distinct from v0.4.20), each cross-model reviewed at a design gate and an implementation gate (gpt-5.5 xhigh; both started NO-GO — the reviewer caught an off-by-one in the grep line-mapping and a missing stream-level test before GO). 🐛 Headline: OpenAI-compatible streaming corrupted multi-byte UTF-8 (CJK / emoji) split across network chunks into � — each HTTP body chunk was from_utf8_lossy'd independently, so a 3-byte Chinese character or 4-byte emoji straddling a chunk boundary broke on both sides (a frequent hit for Chinese users on domestic OpenAI-compatible providers — Kimi/GLM/MiniMax/DeepSeek/Qwen/Doubao — streaming Chinese text); the stream buffer is now raw bytes, decoding only complete SSE lines. A saved OpenAI/custom executor config no longer overrides a shell-set EXECUTOR_PROVIDER — the startup "shell-provided vars win" path had one ungated write that re-pointed EXECUTOR_PROVIDER=anthropic … aris … to OpenAI (wrong executor / model-not-found). An Anthropic stream truncated after content but before a terminal signal now hard-errors (premature_eof) instead of saving a half-finished answer to history as a complete turn (symmetric to the OpenAI #249 guard; the stop_reason-only compat path is preserved, and ARIS_ALLOW_EOF_WITHOUT_STOP=1 opts a terminal-signal-less proxy back into the old behavior). grep_search with multiline: true now matches across lines in content mode (was silently empty — count mode already worked). MCP tool results carried only in structuredContent (empty content) are no longer dropped — the model gets the JSON structured payload. Tests (CI mode): api 32→35 / runtime 205→212 / tools 67 / aris-cli 172→181 / commands 5 (+21, incl. 2 stream-level integration tests), all green. Codex MCP (gpt-5.5 xhigh): design gate (NO-GO → GO after fixing the off-by-one) → implementation gate (NO-GO → GO after adding the stream-level integration tests); the Anthropic streaming spec (every stream ends with message_stop) was WebFetch-verified. Two latent-only candidates (Anthropic block-index routing, OpenAI multi-line SSE) remain deferred.

v0.4.20 (2026-06-19) — bug-fix patch: 7 user-facing bugs surfaced by a Codex adversarial hunt, each reviewed across 3 rounds (the reviewer caught a redraw gap, a trailing-blank, a spinner tail, and a blank-line edge before GO). 🐛 Headline (#299): short REPL replies showed only "✔ Done" — the spinner draws "⠋ Thinking…" with Save/RestorePosition so streamed output overwrites it on the same line, but finish then cleared that whole line, erasing a short single-line reply. The REPL now finishes without clearing when the turn printed visible text (Clear(UntilNewLine) wipes only the spinner tail after the reply). Streamed multi-paragraph replies rendered glued ("para1para2") — each chunk's paragraph separator was trimmed at the stream boundary; the markdown streamer now preserves separators via a held-separator so streamed output equals a single full render (no dangling blank line). Markdown tables with CJK/fullwidth content misaligned — width now counts display cells (CJK = 2), not chars. aris "prompt" / --print ignored the executor model saved by aris setup (REPL-only before) — a configured OpenAI/custom executor got the Anthropic default sent to its endpoint; the one-shot and REPL paths now share one resolver. Esc now actually closes the completion dropdown (it was recomputed right back). glob_search reports the total matched count when truncated (not the capped 100, which made the model think a 1000-match glob had 100 files). /model's custom menu reads the effective env the executor uses, not stale on-disk config. Tests (CI mode): api 32 / runtime 205 / tools 67 / aris-cli 172 / commands 5, all green; +7 new; real-machine verified (short reply renders + "✔ Done"; paragraphs keep their blank lines). Codex MCP (gpt-5.5 xhigh): hunt → 3 review rounds (NO-GO → NO-GO → GO). Two latent-only candidates (Anthropic block-index routing, OpenAI multi-line SSE) deferred to a hardening pass.

v0.4.19 (2026-06-14) — honesty / guardrails patch (theme from a Codex fresh-eyes audit; no behavior change for healthy setups). 🔴 MCP protocol-version negotiation guard — the stdio handshake requested 2025-03-26 but never read the version the server negotiated back (a parsed-but-dead field), so a server agreeing on a version ARIS can't speak was silently accepted and later tools/list / tools/call ran on an incompatible protocol with opaque failures. ARIS now validates the negotiated version against a supported set (2025-11-25 / 2025-06-18 / 2025-03-26 / 2024-11-05 — stdio framing is identical across these) and, on an unsupported one, terminates the child + clears the slot + surfaces a clear per-server error (aris doctor shows it) — the "terminate when versions can't be agreed" behavior the MCP lifecycle spec requires. The request stays 2025-03-26 (proven against codex mcp-server), so healthy servers are unaffected — verified end-to-end: the real Codex MCP server still spawns + initializes + advertises its tools under the guard. 🧹 Papercuts: the OpenAI-family subagent fail-loud message dropped its stale "lands in v0.4.18" marker (now version-agnostic + actionable, still credential-free); OpenAI upstream error bodies are now truncated (500 chars) + credential-redacted (sk-… keys and Bearer … tokens, via a substring scanner that catches the compact-JSON shape {"api_key":"sk-…"} a misconfigured proxy can reflect back) instead of splatted verbatim; the system-prompt hook-events summary now counts only the hooks the runtime actually executes (a command hook with a command string), matching the parser. Tests (CI mode): api 32 / runtime 204 / tools 67 / aris-cli 167 / commands 5, all green; live smoke confirms the real Codex MCP server still initializes under the guard. Reviewed by Codex MCP (gpt-5.5 xhigh): design GO → impl NO-GO (compact-secret miss + command-string strictness) → GO after fixes.

v0.4.18 (2026-06-14) — default model → Claude Opus 4.8, with corrected pricing and a safety net. The bump moves DEFAULT_MODEL, the opus alias, the model picker, aris setup, and the subagent default to claude-opus-4-8 — with an availability fallback: if the account lacks 4.8 (the API returns 404 not_found_error), ARIS auto-falls-back to claude-opus-4-7 for the session, rebuilds the system-prompt model identity so it stays coherent (the model is never told it's 4.8 while served 4.7), warns once, and retries — for the main session (text + JSON) and subagents. It fires only on that precise 404 (never 400/rate-limit/auth), latches against loops, and the text path rebuilds from a pre-turn snapshot so a retry never double-appends the user message; accounts with 4.8 are byte-identical to a plain bump. 💰 Pricing corrected (verified against Anthropic's published schedule; had been a 3–5× over-estimate): current Opus 4.5–4.8 = $5/$25 (deprecated Opus 4/4.1 keep $15/$75, split by word-boundary so a future opus-4-10 isn't mis-tiered); Sonnet 4.x = $3/$15 (decoupled from the generic unknown-model fallback, which stays $15/$75); Haiku was already correct. 🧹 Backlog: aris setup option 10 pins the Codex MCP reviewer to model_reasoning_effort="xhigh" (deterministic for new setups, independent of ~/.codex/config.toml; idempotent merge never clobbers an existing entry); a startup + aris doctor misconfig hint (#259) for a silently-ignored/misplaced config (malformed JSON, or a stray ~/.aris/config.yaml — stderr-only so --print/JSON stdout stays clean); the system-prompt hook summary now marks parsed-but-never-fired events "PARSED ONLY … will NOT run" instead of implying dead hooks run (full event expansion — actually firing SessionStart/SessionEnd/… — deferred to a separate issue). Tests (CI mode): api 32 / runtime 202 / tools 67 / aris-cli 166 / commands 5, all green; a live one-shot smoke returns model=claude-opus-4-8 end-to-end. Reviewed by Codex MCP (gpt-5.5 xhigh) across the design + both implementation batches (design REWORK→GO, impl NO-GO→GO, batch-2 GO).

v0.4.17 (2026-06-13) — the MCP release. Before v0.4.17, mcpServers in settings.json parsed, showed in aris doctor, and did nothing; now ARIS spawns each configured stdio server, runs the MCP handshake, discovers tools, and advertises them as mcp__<server>__<tool> on both provider paths (Anthropic + OpenAI-family), with end-to-end dispatch, soft per-server degradation, and an approval gate for untrusted MCP tools (external processes the sandbox can't cover; --allowedTools now accepts mcp__ names). 🆕 zero-API-key cross-model reviewer: aris setup → option 10 (Codex MCP, ChatGPT subscription, no API key) writes an idempotent mcpServers.codex entry into the settings file the runtime actually reads (atomic write + backup, explicit consent before trust: true), with an optional API reviewer as fallback (ARIS_REVIEWER_PROVIDER=codex-mcp + ARIS_REVIEWER_FALLBACK_PROVIDER); /setup in-REPL rebuilds the system prompt + runtime so reviewer changes take effect without quitting. 🔴 Protocol fix the fakes couldn't catch: real-machine e2e against codex mcp-server exposed that our stdio transport spoke LSP-style Content-Length: framing while the MCP spec (and codex) use newline-delimited JSON-RPC — every fake-server test passed because the fakes spoke the same wrong dialect; writes are now NDJSON, reads auto-detect both, and the spec-mandated notifications/initialized is sent after initialize (a select-based round-trip also closes the #286 large-request deadlock). Hooks: object-style Claude Code hooks preserve matcher / timeout / async (anchored-regex matcher filtering; per-hook timeout, default 30 s kill = warning not deny). Long tail: ARIS_DISABLE_KEYCHAIN gate, Anthropic stop_reason clean-EOF symmetry (CL2), OpenAI tool-call index-missing merge-by-id (OE6), slash commands enter history. Real-machine push-gate hardening (the zero-key reviewer's first run): codex codex/event notification spam silenced by default (gated behind ARIS_MCP_STDERR=inherit), the system prompt now tells the model not to pass a model parameter to Codex (account default = gpt-5.5 + xhigh; arbitrary names are rejected by a ChatGPT account), and a Codex-MCP-primary-with-no-fallback LlmReview call returns a clear "use mcp__codex__codex" message instead of a misleading OPENAI_API_KEY/gpt-5.5 error. Built with the v0.4.16 zero-regression methodology (24 new characterization tests; every deliberate flip annotated in-place). Tests (CI mode): runtime 199 / aris-cli 165 / tools 67 / api 30 / commands 5, all green. Reviewed phase-by-phase by Codex MCP (gpt-5.5 xhigh) across 17 rounds (7 NO-GOs all resolved). Subagent MCP routing (P8) + MCP protocolVersion bump + hook async execution deferred to v0.4.18.

v0.4.16 (2026-05-30) — REPL UX + provider hardening, shipped under a zero-regression discipline: 64 characterization ("golden") tests locked the current provider-routing / pricing / reviewer / subagent / REPL behavior first, then stayed green through every change. Closes #274: command history now persists to ~/.config/aris/history (0600) and reloads on startup, with an ARIS_NO_HISTORY kill-switch and a disk-only secret-skip (credential-looking lines stay in in-session history but never touch disk); bash-style Ctrl+R reverse incremental search (CJK display-width-aware single-line render; no existing key binding changed; no new dependency). Security: an OpenAI-family main session (Kimi / GLM / MiniMax / …) spawning a subagent previously silently billed the user's Anthropic OAuth/Keychain credential — it now fails loud with a clear, credential-free error; full OpenAI-family subagent routing is a cross-crate change deferred to v0.4.17. Groundwork (no behavior change): the 3 byte-identical word-boundary matchers consolidate into one canonical runtime::word_match; new pure ProviderFamily classifier (unwired). Tests (CI mode): runtime 164 / aris-cli 128 / tools 49 / commands 5, all green. Codex MCP (gpt-5.5 xhigh) reviewed each phase + a final integration pass.

v0.4.15 (2026-05-29) — OpenAI-compatible streaming robustness hotfix. Closes #249: MiniMax (and other OpenAI-compatible providers / proxies) were effectively unusable because the clean-EOF completion check treated the data: [DONE] SSE sentinel as the only authoritative signal. A non-empty choices[].finish_reason is the Chat Completions spec's terminal-chunk marker; [DONE] is a transport convention some compatible providers never emit (MiniMax sends finish_reason: "stop" then closes without [DONE]). The clean-EOF decision is now a pure, unit-tested stream_eof_action(...) that completes on EITHER [DONE] OR a non-empty finish_reason; reads are NOT stopped early at finish_reason (a trailing include_usage usage-only chunk is still consumed), genuine truncation still hard-errors, and a pre-output proxy abort still restarts. Coupled fixes: OE7 reads finish_reason before the delta guard (delta-less terminal choice); OE2 flushes pending tool calls on any non-empty finish_reason; OE4 surfaces a mid-stream error envelope as a hard error instead of silently dropping it; OE3 tolerates data:{...} without the space after the colon. +5 unit tests (77→82) extract the previously-untested SSE completion logic into pure helpers. Anthropic SSE path untouched. Codex MCP (gpt-5.5 xhigh) 3 rounds (GO-WITH-NITS → GO-WITH-NITS → GO).

v0.4.14 (2026-05-25) — Security-hygiene release closing the top items from the v0.4.13 codex audit (gpt-5.5 xhigh, 6/10 NEEDS-REWORK verdict). 🔴 S9 (P0) system-prompt config redaction — before v0.4.14, render_config_section() dumped the merged settings.json verbatim into the system prompt sent to the LLM provider, leaking env, mcpServers.<name>.headers.Authorization Bearer tokens, hook command env, signed-URL query params, and apiKey fields. New renderer whitelists top-level fields (model/permissionMode/theme/outputStyle/permissions/sandbox with recursive redaction inside), redacts sensitive keys (apikey/token/secret/password/authorization/headers/env/_KEY/_SECRET/_TOKEN), replaces MCP command with <configured> placeholder, reduces MCP url to strict <scheme://host[:port]> origin (scheme allow-list http/https/ws/wss, ASCII host, digit-only port, IPv6 brackets), and drops hook command strings entirely. Regression test exercises 9 distinct leak surfaces; URL parser has its own targeted test for 7 smuggling attempts including port-position secret injection (codex round-3 catch). 🟡 P9 (P1): DeepSeek aris --help now points at aris setup option 7 instead of an env-var path the resolver never honored. 🟡 M1/M2 (P1) doc: aris doctor + README/README_CN gain experimental warning whenever mcpServers.len() > 0 (full MCP tool dispatch lands v0.4.16). 🟢 C11 (P2) stream idle timeout — both Anthropic MessageStream and the OpenAI SSE loop wrap response.chunk().await in tokio::time::timeout (env ARIS_STREAM_IDLE_TIMEOUT_SECS, default 120, clamp [10, 1800], 0/negative disables); closes the "aris hangs forever with no output" symptom when an upstream HTTPS proxy holds a connection without keepalives. Bundle: 77 skills (+1 /wiki-enrich via late same-day sync to main 7e3ab67 which also picks up upstream check_ready.sh awk + grep-c null-match fix), 54 helpers. Codex MCP 6 rounds (NO-GO + 4 → GO-WITH-NITS + 3 → NO-GO + port smuggling → GO → release metadata GO → sync GO).

v0.4.13 (2026-05-25) — Residue-cleanup release closing every codex audit P1 carried since v0.4.10–v0.4.12, plus the long-tail regression tests. 🟡 v0.4.10 P1.D per-server MCP timeout — mcpServers.<name>.requestTimeoutSecs override > MCP_REQUEST_TIMEOUT_SECS env > 300s default (clamped 1..=1800), so one Codex MCP agent can run 5 min while filesystem MCP errors in 5 s. 🟡 v0.4.10 known limitation closed — McpStdioProcess::request() skips JSON-RPC notifications (id absent/null) and keeps reading until the correlated response. 🟢 meta_opt hook deploy via aris init — tools/meta_opt/{log_event,check_ready}.sh bundle into the binary; aris init writes ARIS-namespaced aris-meta-opt-log-event.sh / aris-meta-opt-check-ready.sh to ~/.claude/hooks/ (codex round-1 #1: never clobbers user hooks); settings.json merge idempotent, backups hard-fail, final rewrite atomic via tempfile + rename. 🧪 9 v0.4.12 targeted regression tests for sandbox.strictMode (3) + parse strictMode + provider_match pricing + has_word o-series + stream_options 400 + meaningful-content classification + premature-EOF retry truth table (codex round-1 #3 — should_retry_on_premature_eof() extracted to pure fn, 7-row test). Bundle: 76 skills, 54 helpers (+2 meta_opt scripts vs v0.4.12). Codex 3 rounds (NO-GO + 3 → NO-GO + metadata → GO).

v0.4.12 (2026-05-22) — Bug-fix + small-feature release. #238 sandbox.strictMode opt-in config key; when set, SandboxConfig::resolve_request() ignores all five LLM-supplied overrides (dangerouslyDisableSandbox, namespaceRestrictions, isolateNetwork, filesystemMode, allowedMounts) — closes the gap where a tool call could silently bypass user sandbox policy. aris doctor adds a "Sandbox:" row; bash tool schema documents the strictMode semantics. #232 auto-review-loop-llm updated from legacy deepseek-chat / deepseek-reasoner (deprecate 2026-07-24; reasoner rejects tool_choice) to deepseek-v4-flash / deepseek-v4-pro. v0.4.10 audit P1 follow-ups: P1.A Anthropic stream retry gates on has_emitted_meaningful_content (a stream that only sent MessageStart before EOF is retry-eligible); P1.B supports_reasoning_effort + reviewer mirror use word-boundary match so openai/o3-mini / proxy:o4 route correctly; P1.C stream_options.include_usage:true proxy fallback retries once without on real 400 unknown-field errors; P2 pricing match precision via provider_match() so qwen3.6-plus / kimi-k2.5 route correctly while my-kimi-clone does not. Skills sync (76 skills, 52 helpers): /interview-cheatsheet + /render-html newly bundled; build.rs ALLOWED_EXTS gains html for render-html templates; EXCLUDED_SKILL_PREFIXES → starts_with("skills-codex"). CI fetch-depth: 0 + origin/main fetch so drift-test ancestor check runs. Cross-reviewed by Codex MCP (gpt-5.5 xhigh) over 4 rounds.

v0.4.11 (2026-05-18) — Skills bundle refresh + sync infrastructure. The embedded skills set in the v0.4.10 binary had fallen behind main (~6 of 56 main skills/ commits had been cherry-picked); v0.4.11 syncs the full set and ships sync infrastructure so the gap can't silently reopen. Bundle: 65→74 user-facing skills, 34→49 helper resources. 10 new skills bundled: /citation-audit (fourth-layer bibliography audit), /experiment-queue (SSH multi-seed job queue with OOM retry), /kill-argument (two-thread adversarial review for theory papers), /resubmit-pipeline (W5: text-only port to a new venue), /paper-talk (end-to-end conference talk pipeline), /slides-polish (per-page Codex layout review), /overleaf-sync (two-way Overleaf Git-bridge), /gemini-search + /openalex (broader literature sources), /qzcli (Qizhi GPU jobs). 46 existing SKILL.md refreshed — most critically the canonical resolver chain rollout (closes real user incident where /research-wiki was empty for a week from hardcoded tools/research_wiki.py), submission assurance gate + external verifier (/paper-writing Phase 6 now functions). tools/ goes 9→18: 9 baseline helpers refreshed (research_wiki.py 315→767 lines with canonical ingest_paper API), 9 new helpers (extract_paper_style.py, figure_renderer.py, paper_illustration_image2.py, overleaf_{setup,audit}.sh, verify_wiki_coverage.sh, watchdog.py, experiment_queue/{build_manifest,queue_manager}.py). New tools/sync_main_skills.sh automates main → bundle rsync with symlink pre-flight + codex-mirror prune + SKILLS_SOURCE_COMMIT pinning. 3 new CI drift tests in crates/runtime/src/cache.rs cover all 4 resolver layer patterns. Gemini MCP calls in /research-lit and /gemini-search now pass model: 'auto-gemini-3' (avoids silent downgrade to 2.5-pro on OAuth-personal capacity exhaustion). CLI runtime unchanged — codex-audit P1 follow-ups remain on v0.4.12 backlog. Cross-reviewed by Codex MCP (gpt-5.5 xhigh) across 5 rounds (REQUEST CHANGES → APPROVE WITH NITS → NO-GO → GO → final GO).

v0.4.10 (2026-05-17) — Stream + MCP reliability + multi-provider pricing. C6 whole-stream restart in Anthropic MessageStream + OpenAI SSE loop on chunk decode failure / premature EOF (ARIS_STREAM_RETRY, default 2, clamp 0..=5, fires only when nothing emitted yet — closes #228-style "error decoding response body" loop). M3 MCP stdio gains 300s default tokio::time::timeout over send+read (override MCP_REQUEST_TIMEOUT_SECS, clamp 1..=1800); response.id ↔ request.id correlation; ensure_server_ready() try_wait() dead-process respawn; kill().await on all failure paths so the next call starts clean (closes #151 / #172 "Calling codex..." stalls). C8/P4 OpenAI streaming requests now send stream_options.include_usage:true + parse cached_tokens; Anthropic streaming merges MessageStart.usage (input/cache) with MessageDelta.usage (output). C9 multi-provider pricing registry (15+ models, OpenAI cache_read = input × 0.1 corrects 5× generic overstatement, DeepSeek cache_hit/cache_miss tiers, has_word() boundary matcher for provider/<model> slugs). 9 dead-code warnings cleared; aris setup help text synced with actual behaviour.

v0.4.9 (2026-05-17) — Closes Codex v0.4.7 audit residuals (L1 TLS double-stack, L3 reasoning_cache compaction misalign, L4 reasoning replay unbounded). 2 new skills bundled (/figure-spec + /paper-illustration-image2 with scripts/ subdirs, new Layer 0b = $ARIS_CACHE_DIR/skills/<name>/scripts/); research_wiki.py promoted to shared tools/ (9+ callers); 5 more SKILL.md migrated to fallback chain.

v0.4.8 (2026-05-17) — Skill helper subsystem rewrite. Bundled helpers extract to ~/.config/aris/cache/<version>/ at startup; every Skill invocation surfaces helperReport JSON + 4-layer resolver preamble; /skills export copies helpers; new integration-contract.md with 6 failure policies; 8 shared helpers (arxiv/deepxiv/exa/S2/openalex/save_trace/verify_papers/verify_paper_audits) bundled; /research-lit + /deepxiv migrated. Plus 4 bug fixes: gpt-5.5+tools 400 on OpenAI; Custom reviewer reset; missing signature field (#228); --version Build date hardcoded.

v0.4.7 (2026-05-16) — DashScope Coding Plan 405 fixed (#159) via native-tls switch (#225); reasoning_content replay for all reasoning models (OpenAI o1/o3/o4 / DeepSeek-R1 etc.), not just Kimi (#226); 600+ lines dead code cleanup + rustyline dep removed + "Claw Code" → "ARIS-Code" rebrand.

v0.4.6 (2026-05-14) — 🚨 Two long-standing silent bugs fixed: PermissionMode::Prompt silently allowed every tool (derived-Ord bug); system prompt hardcoded current_date = "2026-03-31" made models reject post-cutoff data as future/prompt-injection. Plus Custom OpenAI-compatible provider (/setup option 11) with dynamic /models discovery (@Anduin9527 #221 + #222).

v0.4.5 (2026-05-13) — First-class reasoning-model support: thinking content blocks end-to-end (fixes #161) + reasoning_effort='xhigh' for GPT-5.5 / o1 / o3 / o4 / DeepSeek-thinking. DeepSeek V4 Pro + Xiaomi MiMo + Qwen 3.6 + Doubao in /setup (options 7-10). Object-style hooks parser. Default model bumped to Claude Opus 4.7 + GPT-5.5. REPL input hardening (multi-line wrap / Cmd+V paste / CJK boundary). GitHub Actions CI. Credits: @GO-player-hhy (#186), @Jxy-yxJ (#171), @GetIT-Sunday (#216 partial).

Older versions

v0.4.4 (2026-04-20) — Setup UX + reviewer routing fixes (resolves #158, #162) | /setup no longer forces Bearer for Anthropic + custom URL | Provider-aware proxy URL hints | Stale state no longer leaks across provider switches | LlmReview smart fallback

v0.4.3 (2026-04-17) — Third-party Anthropic-compat proxy support (Bedrock etc.) | Skip beta flags that proxies reject | Propagate custom base URL for anthropic provider | Credit @screw-44

v0.4.2 (2026-04-17) — Auto-compaction corruption fix | Compaction summary preserved on OpenAI-compat executors | Shell-provided API keys no longer erased on launch

v0.4.1 (2026-04-15) — Plan mode (/plan) | Cooperative Ctrl+C interrupt | Auto-retry (429/5xx/network) | Research Wiki 📚 (persistent knowledge base) | Self-Evolution 🧬 (/meta-optimize) | Local models (LM Studio/Ollama) | 62 skills synced

v0.3.11 (2026-04-13) — Reviewer Anthropic-compatible mode (Claude via proxy)

v0.3.9 (2026-04-11) — Proxy/custom base URL (CCSwitch) | Local models (LM Studio/Ollama) | Windows (experimental)

v0.3.5 (2026-04-08) — Research Wiki (persistent papers/ideas/experiments/claims + relationship graph) | Meta-Optimize self-evolution (analyze logs → propose SKILL.md patches)

v0.3.0 (2026-04-03) — Multi-file memory index | Rich task system (TodoWrite) | /plan | Security hardening

v0.2.2 (2026-04-03) — /plan step-by-step planning | /tasks persistent tracking

v0.2.1 (2026-04-03) — Persistent Memory | Kimi K2.5 multi-turn fix | CJK cursor fix

v0.2.0 (2026-04-02) — Open source | Kimi + MiniMax + GLM support | Smart LlmReview routing | CI/CD

v0.1.0 (2026-04-02) — Initial release | Multi-executor & reviewer | 42 bundled skills

• 2026-09-28 — 📚 Real papers stop being reported as hallucinated citations (#445, #447, #450; thanks @ilya-pershin and @AfonsoZhang). arXiv sometimes refuses Python's HTTP client with a 406 for minutes while curl gets through; verify_papers.py read that refusal as "paper not found" and one user saw a 47% hallucination rate on 38 real papers. A 406 now goes through curl, and a refusal (406 / 401 / 403) is verify_pending, never unverified. Set SEMANTIC_SCHOLAR_API_KEY and title checks use it. Seen a suspicious hallucination rate recently? Re-run with --no-cache once. Also in this round: five skills can now actually invoke the sub-skills their text tells them to (#440, @Jeremy-xuan); concurrent watchdog registrations no longer overwrite each other (#443, @hiro-nikaitou); xhigh is described as the regular reviewer tier it is (#442, @dreamworld2023).

• 2026-09-16 — 🧩 ARIS is a Claude Code plugin now (#437, thanks @white-drizzle). claude plugin marketplace add wanshuiyin/Auto-claude-code-research-in-sleep → claude plugin install aris@aris → /aris:setup once → restart. Setup registers the Codex reviewer bridge that ships inside the plugin, so the reviewer works on codex-cli 0.154+ out of the box. Plugin skills are typed with the prefix (/aris:idea-discovery); they call each other by short name internally. Codex CLI reads the same repo as a plugin too (codex plugin marketplace add … → codex plugin add aris@aris) and gets the Codex-native mirror. Cursor, Trae and DeepSeek Harness keep their own routes.

• 2026-09-10 — 🔌 codex-cli 0.154 removed codex mcp-server — re-register the codex MCP server. Every ARIS reviewer call went through that entry point; on 0.154+ it now opens the interactive TUI and the MCP handshake fails. ARIS ships its own stand-in, mcp-servers/codex-exec/server.py, same tool names and result shape, driving codex exec underneath — skills unchanged. Run once: git pull in your ARIS clone (older clones do not have the file), then claude mcp remove codex -s user && claude mcp add codex -s user -- python3 "$HOME/aris_repo/mcp-servers/codex-exec/server.py" (absolute path of your clone), then restart Claude Code. Step-by-step for new and existing installs in Quick Start. Works on 0.153 too, so do it before you update. OpenAI's own replacement, the Claude Code plugin, has no ultra effort and no per-thread resume, which the deep-audit skills need. Cursor / Trae / Antigravity / Copilot CLI configs: same key, python3 + that path — see the adaptation docs.

• 2026-09-07 — 🧠 Default reviewer is now gpt-6-astra. Every reviewer call that pinned gpt-5.6-sol now pins gpt-6-astra; the two effort tiers (ultra for the seven deep audits, xhigh everywhere else) are unchanged, and so is the executor — whatever agent you run ARIS in. No access to the model yet? The capability fallback tries gpt-5.6-sol, then gpt-5.5, both at xhigh — nothing to configure.

• 2026-09-06 — 🧹 The installer stops dropping Copilot profiles into every project (#431, thanks @oblivion-1521). Since 2026-08 every run symlinked two Copilot reviewer profiles into your .github/agents/ whether or not anything used them — dead files for Claude Code and Codex users, broken links if you committed them. Now they are deployed only while auto-review-loop is installed; --no-agent-profiles switches them off for good (undo with --agent-profiles). Your next re-run removes the links the installer created earlier; files you wrote yourself are never touched.

• 2026-09-03 — 📣 Papers are launches, not progress reports (rules adopted from anti-defensive-writing-Skill by @Adkid-Zephyr — 🌟 it). The writing contract gains four rules: organize the narrative around the strongest genuine advantage; pick the contest the paper wins; unfavorable numbers stay in the tables, explained as a tradeoff where the evidence supports that and stated neutrally where it does not — never narrated as a defeat; every experiment carries an argumentative duty or leaves the main line; abstract and introduction open with problem → gap → idea → strongest result, and the conclusion never ends on new self-negation. /auto-paper-improvement-loop flags the same defects. Indexed under Awesome Community Skills.

• 2026-08-26 — 🧯 Two over-defense leftovers (#425). /research-review — the one reviewer prompt that never got the scope-limits block — now carries it, and its brief ends with "if the work holds up, say so clearly" instead of bare brutality; the adversarial stance itself is untouched. /research-pipeline no longer dies overnight on a missing VENUE: ideas, experiments, analysis and the narrative report are venue-independent and run to completion — only paper formatting defers, stamped clearly for a later resume. It had also been declaring VENUE = ICLR while forbidding silent defaults; the default is gone.

• 2026-08-26 — ✍️ Papers stop reading like confession letters (#423, #424; several rules adopted from humanize-paper). Claims are stated at the strength the evidence earns; generic caveats ("further research is needed") live in Limitations only; "don't mention X" means X is absent — never "we do not address X" in print; results are ordered by argument, not by the order experiments ran.

• 2026-08-26 — 💡 The idea pipeline stops killing ideas for having neighbors (#419–#422; community reports). ABANDON now has to name the published paper that already contains your result, and concurrent work is a race — your call, not a veto. Brainstorming runs two generator models (gpt-5.6-sol + gpt-5.5) and unions their ideas, aiming for creative direct attacks instead of corner-case stacks. Search digs as hard as ever.

• 2026-08-21 — 🔌 Optional HTTP reviewer fallback for when Codex MCP is unreachable (#413; by @TheFlashForge). Off by default; fires only when Codex provably never got the request — a timeout doesn't count, that could pay twice for two conflicting verdicts. The fallback reads your actual files and gets less trust than Codex, never more.

• 2026-08-21 — 🧹 Four community fixes in one day (#406–#410; by @ZLZLGe and @JasmineLCY). AUTO_PROCEED=true now actually continues on its own; the idea-discovery gate demands a real reviewer receipt, not a checkbox; cached wiki context is scanned right before /idea-creator reads it; Codex users with Claude as reviewer get their three paper skills back.

• 2026-08-09 — 🦆 Copilot CLI defaults /auto-review-loop to its native rubber-duck reviewer (#360, closes #258). Active only inside Copilot CLI sessions; review evidence is revalidated from host events, and same/unknown-family fails closed. The standard Claude Code + Codex setup is untouched.

• 2026-08-09 — 🚧 /idea-discovery can no longer silently skip a stage (#383, closes #285; by @3mom3). Each of the five stages needs recorded evidence, or the report says BLOCKED instead of looking complete.

• 2026-08-05 — 🈶 The research wiki handles non-ASCII (#386, #387; reported by @LIMMIL7). cp936-written wikis were unreadable on other machines, and Chinese-only titles collapsed to <year>_untitled and got deduped away. Existing UTF-8 wikis unaffected.

• 2026-08-04 — 🖼️ Upstream spotlight: posterly — the engine behind /paper-poster-html — shipped a major design upgrade (MIT, by @Chenruishuo; ~50 posters at this year's ICML). GitHub · Blog.

• 2026-08-03 — 🧭 /proof-orchestrator — Workflow 7: proof campaigns with a memory (#381; by @shenmuxing, from their EtaSkill). Stateful local-first proof runs that continue across sessions, with a ready-to-paste GPT Pro handoff when a proof stalls. /proof-checker remains the submission gate.

• 2026-07-15 — 🔗 Double-blind citation field audit (#371). New /citation-crosscheck: two agents work blind — one reads each cited entry from the local .bib, one re-fetches it from the web — and a deterministic gate diffs them field by field (author set+order, year, venue, arXiv-id/DOI), emitting a side-by-side .xlsx with MATCH/MINOR/MISMATCH. Complements /citation-audit (context-fit); this owns field accuracy.

• 2026-07-14 — 🐞 /web-debug-search (Issue #211). Adds a focused debugging/discovery workflow for GitHub Issues and Discussions: exact and normalized error-string matching, version compatibility tracking, and explicit failure handling. Results are labeled for debugging only and are not paper-citation evidence.

• 2026-07-14 — 🧩 Selective install + global helper pointer (#366). The 81 skills are no longer all-or-nothing — all four installers support group/skill-level picks (--list-groups, --groups X,Y, --skills X, --exclude Y, or a bare-TTY checkbox picker), with hard pipeline deps auto-included. Updates now confirm each NEW upstream skill individually (--add-new / --skip-new for scripting; declines are remembered and never re-asked). Also fixes copy installs (~/.claude/skills) losing helper-script resolution, via a new ~/.aris/repo pointer file. ⚠️ Backward compatible — --quiet fresh installs still install everything; run any installer/updater once to pick up the pointer file. Selective install →

• 2026-07-12 — 🛡️ Your paper now gets the reviewer-side forensics treatment before you submit (#357). New /integrity-forensics skill: a SHA-pinned thin launcher runs Anti-Autoresearch's hostile-reviewer sweep (evidence ledger, nine auditor dimensions, numeric core, rules-only adjudicator) on your paper first. The verdict feeds a typed gate — flags can block a submission, a clean sweep is recorded as "no new blocker" (never an acquittal) — and findings close only with typed, hashed evidence or a recorded human waiver (rewording the flagged sentence doesn't count; the ledger notices). /paper-writing runs it by default at submission assurance (— self_forensics: false opts out; the Codex mirror is opt-in and limited to upstream's deterministic slice, which can flag but never say CLEAN). ⚠️ First run clones and validates the pinned upstream (needs network); run bash tools/smart_update.sh --apply.

• 2026-07-10 — 🧠 Reviewer default is now GPT-5.6-Sol; deep audits think at the new ultra level (#354). codex-cli 0.144.1 added max/ultra reasoning above xhigh; ARIS reviews now default to gpt-5.6-sol, with the seven heavyweight verdicts (/proof-checker, /kill-argument, /research-review, /experiment-audit, /paper-claim-audit, /result-to-claim, /meta-apply) at ultra and everything else at xhigh. Older codex-cli or no model access steps down automatically (5.6-sol → 5.5, both xhigh) — never below xhigh, never on a mere timeout. Also fixed: /result-to-claim now stops honestly instead of judging its own results when the reviewer is unreachable. ⚠️ Upgrade codex-cli to ≥ 0.144.1, restart the session (MCP reloads only then), and run bash tools/smart_update.sh --apply.

• 2026-07-03 — 🧬 Three small updates adapted from Anthropic's Claude Science skills (#339, #340, #341; Apache-2.0). ARIS now has one shared way to describe GPU environments, so the same setup can be reused across SSH machines, Modal, and clusters, then checked by a fresh agent following the setup notes. We also added a small tool that tests whether a skill description actually makes the right skill get picked. Finally, figure and writing checks now separate facts from style: truth checks must pass, style advice stays optional. ⚠️ Run bash tools/smart_update.sh --apply to pull.

• 2026-07-02 — 🔁 Ideas from Karpathy's LOOPS.md, brought into ARIS (#333–#337). Reviewers now start by looking for what may be wrong, not by giving a polite score. If a review result looks strange, ARIS points you to the saved reviewer transcript before you ask the model again. A failed build can be restarted from the plan instead of endlessly patched, while plans, logs, and results are kept. Scoring can now use real good and bad examples, /meta-optimize asks what can be removed, and /paper-writing agrees on a clear "done" checklist before drafting starts. ⚠️ Run bash tools/smart_update.sh --apply to pull.

• 2026-06-20 — 📚 Research wiki: all four node layers now have deterministic writers — fixes "re-generated ideas not recorded" (#305, #306, #307, #308). A user hit a real bug — ideas recorded on the first /idea-creator run vanished on re-generation — because wiki pages were written freehand, a prose step the model skips on a re-prompt. Each layer now has a dedicated research_wiki.py writer joining ingest_paper: add_claim (claims born at /proof-checker), upsert_idea (/idea-creator), add_experiment (/result-to-claim) — each guarded by a drift-check so it can't silently regress to dead code. A claim's status is now a strict proof axis (verified/refuted/unproven/…) while experiment support is carried by supports/invalidates edges (closing a latent contradiction the shared validator rejected), and the Codex-CLI skill mirror is synced to match. Zero behavior change when no research-wiki/ is present.

• 2026-06-19 — 🛰 Overnight loops can now notice when they die or get stuck (#300, #301, #302; adapted from operational patterns in Deli Chen's AutoResearch). A new watchdog checks whether an unattended loop is still updating its state file and writes an alert when it goes quiet; it only reports the problem, never restarts a verdict-bearing run. A separate iteration log watches for rounds that stop finding anything new: two empty rounds force a change of direction, four call in a human, and the cross-model jury still decides whether the result is actually good enough.

• 2026-06-07 — 🖼️ /paper-poster-html is now the default poster pipeline; the old LaTeX /paper-poster is retired. It builds the poster as one HTML/CSS file at the venue's real print size, then runs measured layout and asset checks before a content reviewer sees it, so review time goes to the science instead of crooked columns. It also ships templates, reusable poster components, and venue token packs; the core gate machinery was adapted from posterly (MIT, by @Chenruishuo). ⚠️ /paper-poster now redirects to /paper-poster-html; the LaTeX pipeline lives only in git history.

• 2026-05-31 — 🤝 Two community tools worth a look. Claude Fleet (@tianyilt) is a local read-only dashboard for keeping track of many Claude Code / Codex windows at once. posterly (@Chenruishuo) builds conference posters as a single HTML/CSS file and exports a print-ready PDF through headless Chromium, no LaTeX needed. Both are listed under Awesome Community. 🌟 if they help you.

• 2026-05-31 — 🛰 Fourth reviewer backend: Gemini via Antigravity CLI (#267 by @ZGJY95). — reviewer: agy routes review through the Antigravity CLI for users without Codex MCP / Oracle — fail-closed on the cross-model invariant (recovers + verifies the real Gemini-family model, refuses non-Gemini, binds the recovered transcript to the call via a user-event nonce). Wired into reviewer-routing.md.

• 2026-05-29 — ⚙️ ultracode-native convention layer — fan out for breadth on any runtime tier, keep the cross-model jury sacred. Three new shared-references docs decouple breadth from verdict: fan-out-pattern.md (skills generate candidates across same-family Claude subagents — Tier-1 Workflow / Tier-2 Agent / Tier-3 sequential — all ending in the identical cross-model jury), acceptance-gate.md ("a loop can DRIVE, it cannot ACQUIT" — self-judge execution-completeness, never quality/correctness), and external-cadence.md (/loop & CronCreate are fire-control, never a jury). Wired into /idea-creator, /research-lit, /proof-checker, /kill-argument (fan-out) plus 16 skills (cadence fence/affordance). Also stripped 48 vestigial Agent grants (least-privilege + a drift-check guard), fixed /idea-creator's same-family idea pre-filter, and reconciled an /auto-review-loop OR→AND stop-condition inconsistency. Non-ultracode users benefit immediately — fan-out degrades to sequential with the same final jury.

• 2026-05-28 — 📝 First blog shipped: A Survey on Continuous DLM (2026 H1, 6 papers) — long-form bilingual technical survey by Ruofeng Yang (SJTU), written end-to-end through the ARIS-in-AI-Offer workflow (Claude Opus 4.7 + Codex GPT-5.5 xhigh + Gemini auto-gemini-3 cross-model discussion). Compares ELF, ByteDance Cola-DLM, and Flow-Matching family across discrete-DLM problems, the "known-unknown" continuous space idea, training pipeline, architecture / params / shapes, inference grids + Tab 6/7 numerical results, denoising trajectories, and a Field Landscape against Cola-DLM. A 1.7 MB self-contained HTML (no build) — demonstrates the kind of long-form analysis the /render-html toolchain can produce.

• 2026-05-26 — 🌐 HTML auto-emission activated at 8 workflow checkpoints. /idea-discovery, /auto-review-loop, /research-pipeline, /kill-argument, /proof-checker, /paper-claim-audit, /citation-audit, /rebuttal now auto-render their primary MD artifact to a single-file HTML view via /render-html. Cost-tiered: interim views use --no-review, audit-class / reviewer-facing deliverables keep the full Codex render-fidelity gate. Default on (RENDER_HTML = true); per-skill opt-out. Failures non-blocking — source MD stays canonical.

• 2026-05-26 — 🤝 Community PR wave — 5 merges this week. /wiki-enrich (#247 by @hungchun0201) fills paper TODOs ingest_paper leaves as scaffolds — Karpathy LLM-wiki principle, fetch chain alphaxiv→deepxiv→arXiv. Mirror drift checker + CI (#241 by @VeraPyuyi) keeps main↔mirror in sync. /research-pipeline Stage 2/3 unified into /experiment-bridge delegation (#243 by @ZBigFish) — old inline was a strict subset of the bridge. Windows PowerShell installer parity with reparse-chain inside-repo guard + -FromOld legacy migration + Windows CI matrix (#242 by @VeraPyuyi). Plus manual-review MCP (#246 by @ZBigFish) — third reviewer backend — reviewer: manual for zero-cost cross-model review (paste prompt to any non-Claude model: DeepSeek / Kimi / ChatGPT / Gemini / local llama); cross-model invariant guarded by bilingual UI banner + per-session token auth + fail-closed when MCP unavailable.

• 2026-05-17 — 🐙 GitHub Copilot CLI adaptation — native SKILL.md + MCP support, no skill mirror needed. Installer (install_aris_copilot.sh) + smart-updater + 13-test suite. Community contribution by @EarendelH (#229, closes #214 / #227 / #203).

• 2026-05-17 — 🛠 Tools-stability roadmap (Phase 1+2+3) complete (closes #176 / #177 / #178). Community reported that helper scripts weren't propagating into user projects after install_aris.sh. Phase 1 — every SKILL.md caller of the 10 canonical helpers now resolves via the strict-safe 3-layer chain .aris/tools/ → tools/ → $ARIS_REPO/tools/ documented in integration-contract.md §2 (which also defines 5 failure policies A/B/C/D1/D2/E). Phase 2 — new advisory CI lint catches hardcoded python3 tools/foo.py patterns in PR-modified SKILL.md (advisory only, never fails CI). Phase 3 — three single-owner helpers (figure-spec, paper-illustration-image2, experiment-queue) moved into their SKILL's scripts/ subdirectory; owner SKILLs use Layer 0 ${CLAUDE_SKILL_DIR}/scripts/ ahead of the canonical chain; legacy tools/ paths retained as os.execv Python forwarding shims. ⚠️ Existing users: no action needed — legacy tools/ entries are now shims. If you haven't run install_aris.sh since 2026-04-30, one idempotent rerun catches everything up.

• 2026-05-14 — 🩹 /paper-plan + /paper-write learn GAP_REPORT.md + <!-- DATA_NEEDED --> discipline (#217). When — style-ref: is set and the user's project has structural assets (figures/, results/, NARRATIVE_REPORT.md, etc.), /paper-plan emits a Gap Report mapping the exemplar's section topology + density (from style_profile.md) against your actual assets — surfacing slots you have no evidence to fill (e.g., "exemplar has 3×4 ablation table, you have no ablation data"). Then /paper-write writes <!-- DATA_NEEDED: <Slot ID> — <description> --> HTML comments instead of fabricating content at missing slots — invisible in the compiled PDF, grep-friendly for human triage / /experiment-bridge follow-up. Narrow carve-out from the "no placeholders" rule, scoped to GAP_REPORT-listed slots only. Original idea by @zhangpelf.

• 2026-05-14 — ⚙️ Default reviewer model: gpt-5.4 → gpt-5.5 across ~30 SKILL.md REVIEWER_MODEL defaults. Codex MCP has routed gpt-5.5 as the default since 2026-04-24; this catches the docs up to runtime. ⚠️ Behavior changes: (a) .aris/traces/* JSONs from prior runs are not reproducible — re-runs on 5.5 may emit different WARN/FAIL verdicts on borderline cases (reviewer-quality lift, not regression). (b) ChatGPT Plus/Pro monthly quotas drain faster under heavy use. Fallback: pass — reviewer-model: gpt-5.4 per invocation, or pin REVIEWER_MODEL = gpt-5.4 per skill. Oracle Pro tier (routed via — reviewer: oracle-pro) is a separate path and unaffected.

• 2026-05-13 — 🔍 tools/verify_papers.py + Pre-Search Verification Protocol — anti-hallucination filter for literature-facing skills. New helper does 3-layer fallback verification (arXiv batch API up to 40 IDs/request → CrossRef DOI lookup → Semantic Scholar fuzzy title match, default 0.6 word-overlap) and emits 4-state per-paper status (verified / unverified / verify_pending / error) plus a top-level verdict aligning with assurance-contract.md (PASS / WARN / BLOCKED / ERROR). Transient failures (5xx, timeouts, 429) are tagged verify_pending and excluded from the hallucination rate so network blips don't get conflated with fabricated references. Per-project cache at <project>/.aris/cache/verify_papers.json with 30-day TTL; canonical key priority arxiv:{id_without_version} → doi:{lowercase} → title:{sha1[:16]}. New Pre-Search Verification Protocol subsection in shared-references/citation-discipline.md makes the split explicit: this protocol is the fast filter between SEARCH (Step 1) and full VERIFY (Step 2); /citation-audit and /paper-claim-audit remain the submission-time audit gates and are not replaced. /research-lit gets a mandatory Step 1.5: Verify Candidate Papers calling the helper; /idea-creator and /novelty-check add a Key Rule reference for cited Closest Prior Work / landscape entries. Unverified papers are retained in output tagged [UNVERIFIED] (retention-over-silent-removal) so search-quality issues stay visible. Set ARIS_VERIFY_EMAIL in your shell to lift CrossRef to the polite-pool rate. Original signal from @YiwenZhu77 in #120 — landed via clean reimplementation rather than direct merge (PR was 5 weeks old + scope creep into figure-style).

• 2026-05-06 — 🎤 /paper-talk workflow + /slides-polish skill — end-to-end conference talk pipeline. /paper-talk orchestrates paper → slide outline → Beamer + PPTX → per-page polish → assurance audits → final report (sister to /paper-writing, /paper-poster); composes /paper-slides, /slides-polish, plus /paper-claim-audit + /citation-audit when assurance: conference-ready. /slides-polish is the post-generation visual pass: per-page Codex review against a reference PDF + a fix-pattern catalog (PPTX font scaling 1.5-1.8× for projector-readable size, text-frame resize after font bump, banner-as-tcolorbox, italic style leak guard, em-dash spacing, Chinese EA font hint via PingFang SC, anonymity placeholder discipline). Assurance ladder draft / polished (default) / conference-ready is independent from the effort axis; effort: lite, assurance: conference-ready is legal and means "fast pipeline, every audit must emit verdict before final". Phase 4 staging adapter materializes slide text + speaker notes + talk script as a synthetic paper directory (.aris/paper-talk/audit-input/sections/*.tex + symlinked .bib / results/ / figures/) so the existing audits run with their paper-shaped contracts and emit 6-state JSON verdicts per shared-references/assurance-contract.md.

• 2026-05-05 — 🔁 /resubmit-pipeline — Workflow 5: text-only resubmit across venues (#208). Port a polished paper from one venue to another under hard constraints (no new experiments, no bib edits, no framework changes, never overwrite prior submissions). 5 phases: physical isolation → 5-layer anonymity check → audits (proof / claim / citation --soft-only) → microedits via /auto-paper-improvement-loop --edit-whitelist with per-round diff gate → adversarial gate via /kill-argument → final compile + Overleaf push via /overleaf-sync. Two prerequisite SKILL upgrades shipped in the same PR: /auto-paper-improvement-loop --edit-whitelist <path> (YAML schema with allowed/forbidden paths + forbidden_operations like new_cite / new_theorem_env / numerical_claim, forbidden_deletions, requires_user_approval_for, max_edits_per_round) and /citation-audit --soft-only (translates KEEP/FIX/REPLACE/REMOVE verdicts to text-rewrite proposals when bib is frozen; hallucinated citations get drop_cite_in_body_only action). Master RESUBMIT_REPORT.json ledger per shared-references/assurance-contract.md; 7-verdict failure mode table including USER_DECISION runtime state.

• 2026-05-05 — 🗡 /kill-argument — adversarial Attack-Adjudication review for theory papers (#206). Two fresh codex 5.5 + xhigh threads: Thread 1 writes the strongest 200-word rejection memo a senior area chair would produce; Thread 2 (independent adjudicator, NOT defender) reads the current paper and classifies each rejection point as answered_by_current_text / partially_answered / still_unresolved with file:line evidence. Output: KILL_ARGUMENT.{md,json}, detect-only. Integrated as Phase 5.6 of /paper-writing (between claim-audit and citation-audit) and as the canonical implementation called from /auto-paper-improvement-loop Step 5.5 — replaces inline prompt in both places. Mandatory at assurance: submission for theory-heavy / scope-heavy papers; emits NOT_APPLICABLE for empirical papers without scope claims. Audit JSON is verify_paper_audits.sh-compatible (full schema per shared-references/assurance-contract.md, 6-state verdict). Catches the failure mode score-based reviews miss: when every local component is correct (numbers match, cites resolve, theorems prove) but the paper still oversells what it actually establishes.

• 2026-05-04 — 🪲 /research-wiki and 8 caller skills now resolve helper via fallback chain (#204). Bug: after bash tools/install_aris.sh the helper lives at .aris/tools/research_wiki.py (symlink), but skills hard-coded tools/research_wiki.py and silently failed when invoked — research-wiki/ stayed empty across full W1 runs. Fix: 3-layer chain (.aris/tools/ → tools/ → $ARIS_REPO/tools/) codified in shared-references/wiki-helper-resolution.md. The manual-copy workaround at <project>/tools/research_wiki.py is layer 2, so users who cp-installed the helper as a temporary fix continue to work. ⚠️ Existing users: rerun bash tools/install_aris.sh once — also picks up a separate Python 3.9 ImportError fix in the helper.

• 2026-05-03 — 🎨 Opt-in — style-ref: <source> for writer-side skills (#202). /paper-{plan,write,writing,illustration,poster,slides}, /grant-proposal, and /auto-paper-improvement-loop accept an optional — style-ref: <source> argument that mimics a reference paper's structural style (section ordering, theorem/figure density, sentence cadence, citation style) without copying its prose, claims, or terminology. Sources: local .tex dir/file, local PDF, arXiv id (2501.12345 or arxiv:2501.12345), HTTP/HTTPS URL. Overleaf URLs/IDs are rejected — clone via /overleaf-sync setup <id> first. Default OFF; existing behavior unchanged when the flag is absent. Reviewer / auditor sub-skills (/proof-checker, /paper-claim-audit, /citation-audit, the improvement-loop reviewer) never see the style ref — cross-model review independence preserved. ⚠️ Existing ARIS users: the helper ships at tools/extract_paper_style.py, distributed via the .aris/tools symlink (install_aris.sh Phase 0, added in #192). Re-run bash tools/install_aris.sh once to refresh the symlink and pick up the helper. Manual fallback: cp <ARIS-repo>/tools/extract_paper_style.py <your-project>/tools/. Without either, the writer skill aborts with a clear error pointing here.

• 2026-05-02 — 🪨 Community spotlight: rosetta by @SyntaxSmith. Programmatic access to ChatGPT Pro / gpt-5.5-pro / DeepResearch from Node, via Chrome CDP Fetch interception + WebSocket second-leg streaming; ships an MCP server for Claude Code / Codex / Cline. Alternative implementation path to Oracle MCP for ARIS users invoking — reviewer: oracle-pro — same target capability (Pro-tier reviewer), different mechanics. Indexed under Awesome Community Skills & Extensions. 🌟 if you're using it!

• 2026-05-02 — 💎🧿 Model & MCP routing updates. (a) /gemini-search default bumped to gemini-3-pro-preview (strongest Gemini, out-of-box). ⚠️ Action required: requires gemini-cli v0.40+ (run gemini --version; upgrade with npm i -g @google/gemini-cli if older). Legacy override: /gemini-search "topic" — model: gemini-2.5-pro. Other overrides: gemini-3-flash-preview (faster), auto-gemini-3 (load-routed). (b) /idea-discovery Phase 1 now includes Gemini in its literature survey by default (#199) — auto-injects — sources: all, gemini into /research-lit unless the user passed an explicit — sources:; graceful skip if gemini-cli not installed. (c) Oracle MCP upstream PR queue (steipete/oracle/pulls) is the first triage stop when invoking — reviewer: oracle-pro (especially o3-deep-research / gpt-5.5-pro) — ARIS does not vendor Oracle MCP; check upstream first if behavior surprises you (reviewer-routing.md)

• 2026-05-02 — 🛠️🔗 Tools-infrastructure migration started. (a) install_aris.sh creates optional .aris/tools symlink (#192, closes #174) — Phase 0 of the 4-step tools-stability plan (#174 → #176 → #177 → #178); idempotent, zero impact until rerun. (b) /experiment-queue orchestration paths repaired (#193) — first real user of the symlink; 7 cascading bugs fixed via 3 rounds of Codex MCP gpt-5.5 xhigh audit. Pure prose + docstring; queue_manager.py logic untouched. Windows install_aris.ps1 parallel update tracked as follow-up

• 2026-05-02 — 🔬 Three new opt-in audit flags via fast-path delegated-agent workflow (#187, #188, #189). /citation-audit --uncited surfaces bib entries with no \cite{} reference (detect-only). /proof-checker --deep-fix adds a repair-grade plan to the Phase 1 reviewer prompt (corrected statement / patch plan / closure tests + Schur/quadratic-form algebra sanity). /proof-checker --restatement-check adds Phase 3.6 cross-location theorem drift detection (6 drift signatures). Zero behavior change when flags unset. Plus doc PRs #190 (thread-policy) + #191 (auto-loop xref). Delegated-agent + maintainer-fixup pattern; Codex MCP gpt-5.5 xhigh review caught 6+ blockers

• 2026-05-01 — 🔍 Gemini + OpenAlex literature sources for /research-lit (#175, community contribution by @stdAri). Two opt-in sources: /gemini-search (AI-driven discovery via jamubc/gemini-mcp-tool MCP) and /openalex (250M+ work open citation graph, no API key). Triggered via — sources: gemini or — sources: openalex; zero behavior change when default all (both excluded). Maintainer fixups: corrected @google/gemini-cli npm name; added try/except ImportError + bash preflight for graceful OpenAlex skip when requests missing

• 2026-04-30 — 📝 /rebuttal per-reviewer thread mode + transferable patterns (SKILL.md). Adds VENUE_MODE (single_document | per_reviewer_thread) for OpenReview-style venues, reviewer_priority: pivotal routing, structural_distinction response mode, 5 reviewer-defensive heuristics, 2 Phase 5 lints, and severity-scaled stress rounds. Default VENUE_MODE = single_document keeps ICML-style behavior — zero change for existing users. Three rounds of cross-model review before/after merge

• 2026-04-30 — 🪞 Codex skill mirror rebuilt + dedicated install/update chain (#179, community contribution by @No-518). skills/skills-codex/ now mirrors all 67 mainline skills; replaces mcp__codex__codex reviewer path with Codex-native spawn_agent + send_input. New tools/install_aris_codex.sh + tools/smart_update_codex.sh handle project-local symlinks with manifest tracking. Anti-drift: tests/test_codex_skill_mirror.py + tests/test_codex_install_update.py (26 failure paths). Open discussion in #184

• 2026-04-24 — 🎨 /paper-illustration-image2 — Codex-native image generation as Phase 2b illustration backend (#166, community contribution by @kbr19-thu 清华). Uses ChatGPT Plus/Pro quota via local Codex app-server MCP bridge — no GEMINI_API_KEY required. Triggered by /paper-writing — illustration: codex-image2; default stays figurespec (zero behavior change). Async-only API, sandboxed writes to figures/ai_generated/, integration-contract-compliant helper. Marked experimental (Codex debug app-server is unstable upstream)

• 2026-04-21 — 📚 Research Wiki ingest actually works now (research_wiki.py, /research-wiki). Fixes user-reported bug where /research-wiki init left papers/ empty forever (ingest subcommand had no implementation; paper-reading skills had no wiki hook). New canonical python3 tools/research_wiki.py ingest_paper helper owns slugging / metadata fetch / dedup / page render; all 6 paper-reading skills wired to it. Manual backfill via sync --arxiv-ids or sync --from-file. Ships with integration-contract.md formalizing the six-component pattern every cross-skill integration must follow

• 2026-04-21 — 🛡️ Assurance Gate: — effort: beast | max now really runs mandatory audits (assurance-contract.md, tools/verify_paper_audits.sh). Fixes silent-skip of /proof-checker / /paper-claim-audit / /citation-audit at high effort. New assurance axis (draft | submission) independent from effort: lite / balanced → draft (zero behavior change), max / beast → submission. At submission the 3 audits emit a JSON artifact with 6-state verdict; paper-writing Phase 6 runs the external verifier as source of truth (non-zero exit blocks Final Report). SHA256 input hashing catches stale audits. Escape hatch: — effort: beast, assurance: draft

• 2026-04-20 — 🩹 Project install: flat layout + manifest tracking — fixes a real bug where the previous nested install (.claude/skills/aris/) hid skills from Claude Code's slash-command discovery (CC only scans one directory level). Anyone who ran install_aris.sh before this date was silently affected. New install_aris.sh creates one symlink per skill at .claude/skills/<name>, writes a versioned manifest to .aris/installed-skills.txt, and is re-runnable to reconcile new/removed upstream skills. Defense-in-depth: 13 safety rules (no-symlinked-parents, exact-target revalidation, slug regex, atomic same-dir manifest rename, no-overwrite-real-files, mkdir-based portable lock, ADOPT for crash recovery, …). Granular --adopt-existing / --replace-link flags replace the all-or-nothing --force. Migration paths: --from-old for legacy nested symlink, --migrate-copy keep-user|prefer-upstream for legacy nested copy. smart_update.sh --target-subdir .claude/skills/aris is now deprecated with a redirect to install_aris.sh. Stale-file bug in cp -r overlay also fixed (now rm -rf && cp -r for safe-update path)

• 2026-04-19 — 🔗 /overleaf-sync — two-way bridge between local ARIS paper directory and an Overleaf project via the official Overleaf Git bridge (Premium). Lets collaborators keep editing in the Overleaf web UI while ARIS audit/edit pipelines (/paper-claim-audit, /citation-audit, /auto-paper-improvement-loop) keep running locally. Sub-commands: setup (one-time, user-driven so the agent never sees the token) / pull (with diff-protocol — flags half-sentences, typos, claim/cite changes that should re-trigger audits) / push (with confirmation gate before writing to shared Overleaf state) / status (3-way divergence check). Token never touches the agent or any file — primed once into macOS Keychain via the user's terminal, then auth-free for all subsequent agent operations

• 2026-04-19 — 📚 /citation-audit — fourth and final layer of the evidence-and-claim assurance stack (experiment-audit → result-to-claim → paper-claim-audit → citation-audit). Fresh cross-family reviewer (gpt-5.4 via Codex MCP) with web/DBLP/arXiv lookup verifies every \cite{...} along three independent axes: existence (paper resolves at claimed arXiv ID/DOI/venue), metadata correctness (authors/year/venue/title match canonical sources), and context appropriateness (the cited paper actually establishes the claim it supports — the most diagnostic check). Per-entry verdicts: KEEP / FIX / REPLACE / REMOVE. Auto-integrated into Workflow 3 Phase 5.8 as the pre-submission bibliography gate. Empirical motivation: in a real submission run, several real papers were cited in contexts they did not actually support, and at least one entry shipped with author = "Anonymous" — none caught by metadata-only checks

• 2026-04-17 — 🔀 /experiment-queue integrated into Workflow 1.5 + research-pipeline — experiment-bridge Phase 4 Deploy now auto-routes by milestone job count: ≤5 jobs → /run-experiment, ≥10 jobs or phase dependencies → /experiment-queue (with OOM retry, stale-screen cleanup, wave-transition gating, crash-safe state). New --- batch: queue override for global force-queue mode. Large multi-seed sweeps from EXPERIMENT_PLAN.md (e.g., 36-cell N × seed × n_train grids) now get proper orchestration without manual queue invocation

• 2026-04-17 — 🔗 Project-local symlink install (resolves #118) — new recommended default install. bash tools/install_aris.sh auto-detects platform (Claude Code / Codex CLI), creates .claude/skills/aris or .agents/skills/aris symlink to the ARIS repo, adds a managed <!-- ARIS:BEGIN --> block to CLAUDE.md / AGENTS.md telling the agent to use only project-local skills, and records install metadata in .aris/skill-source.txt. Solves the skill collision problem when ARIS is mixed with Superpowers / OpenHands / other community packs in the same global skill directory. PowerShell version (install_aris.ps1) ships with junction support for Windows. smart_update.sh --target-subdir flag added for .agents/skills/aris (Codex) project-copy installs; symlinked installs now correctly refuse smart_update and direct users to git pull. Global install remains supported for power users

• 2026-04-16 — 🎨 /figure-spec — deterministic JSON→SVG renderer packaged as a first-class skill. Preferred default for architecture/workflow/pipeline/audit-cascade figures in papers. Shape-aware edge clipping (rect/circle/ellipse/diamond), self-loops, curved edges, multi-line labels with CJK width estimation. Editable vector output, reproducible (same spec → same SVG), no external API. Phase 2b in Workflow 3 restored: illustration: figurespec (new default) / gemini / mermaid / false — 4-way illustration selector with complementary strengths

• 2026-04-16 — ⚙️ /experiment-queue — SSH job queue for multi-seed/multi-config ML experiments. Designed from real 36-cell NeurIPS sweep pain points: OOM-aware retry with backoff, stale-screen cleanup, wave-transition race prevention, teacher→student phase dependencies, crash-safe scheduler that resumes from JSON state. Declarative grid specs expand automatically (e.g., N × seed × n_train → 36 jobs). Configurable conda_hook + gpu_free_threshold_mib for non-standard environments. Use for ≥10 jobs; /run-experiment stays for ad-hoc

• 2026-04-15 — 🛡️ Paper Writing Pipeline Hardening — 10 empirically-motivated patches from a real NeurIPS run. REVIEWER_BIAS_GUARD=true: every review round uses a fresh thread (codex-reply inflated 3→8/10). Reviewer Independence Protocol: no fix summaries to reviewer. Step 4.5 Restatement Regression Test: catches theorem drift across fix rounds. Step 5.5 Kill Argument Exercise: final-round adversarial attack/defense for theory papers. Location-aware overfull blocking. Theory Paper Consistency Pass in /paper-write. Enforced Bib Hygiene with DBLP/CrossRef validation. Phase 5.5 Mandatory Final Claim Audit as submission gate. Review Tracing Protocol: full prompt/response pairs saved to .aris/traces/ for reviewer-independence audit (review-tracing.md, save_trace.sh). Inspired by community contribution from @李傲龍

• 2026-04-15 — 🎨 FigureSpec Renderer v2 — deterministic JSON→SVG figure generation for academic papers. Shape-aware edge clipping (rect/circle/ellipse/diamond), self-loops, curved edges, multi-line labels with CJK width estimation, comprehensive validation (type checks, structure, palette). Went through 5 rounds of Codex review (3/10→7/10). All architecture and workflow diagrams in the ARIS tech report were generated with this pipeline. New --- mode: vector for /paper-illustration skill

• 2026-04-14 — 📋 /paper-claim-audit — zero-context paper-to-evidence verification. Fresh reviewer with NO prior context compares every number in the paper against raw result files. Catches rounding inflation, best-seed cherry-pick, config mismatch, delta errors, scope overclaim. Auto-integrated into Workflow 3 (Phase 4.7). Completes the 3-layer audit chain: /experiment-audit (code) → /result-to-claim (science) → /paper-claim-audit (reporting). 👁️ Visual PDF review also added to improvement loop — reviewer now sees compiled PDF, not just LaTeX source. Inspired by Hermes Agent

• 2026-04-13 — 🧿 GPT-5.4 Pro via Oracle — — reviewer: oracle-pro on any skill for the strongest available reviewer. API mode (fast) or browser mode (free). Supported on: /research-review, /auto-review-loop, /experiment-audit, /proof-checker, /rebuttal, /idea-creator, /research-lit. Default stays Codex xhigh. Not installed = zero impact. Setup →

• 2026-04-13 — 🔬 /proof-checker — rigorous mathematical proof verification via cross-model review. 20-category issue taxonomy, two-axis severity, side-condition checklists (DCT/MCT/Fubini/IFT/...), counterexample red team, proof-obligation ledger. Auto-integrated into Workflow 3: detects \begin{theorem} and runs before improvement loop. Complements /proof-writer

• 2026-04-10 — ⚡ Effort Levels — — effort: lite | balanced | max | beast. Controls work intensity across all skills: papers found, ideas generated, review rounds, writing depth. Codex reasoning stays xhigh always. beast = every knob to maximum for top-venue sprints. Default balanced = zero change for existing users. Details →

• 2026-04-10 — 🔎 DeepXiv integration — progressive paper retrieval via DeepXiv CLI. Opt-in: — sources: deepxiv or — sources: all, deepxiv. Staged reading: search → brief → head → section. pip install deepxiv-sdk to enable. Community contribution by @DreamEnding

• 2026-04-10 — 🛡️ /experiment-audit — cross-model experiment integrity verification. GPT-5.4 reads your eval scripts and results directly, checks for fake ground truth, self-normalized scores, phantom results, and scope inflation (#131, #57). Advisory — warns loudly, never blocks. /result-to-claim auto-reads audit if present. New experiment-integrity.md shared reference. The executor must never judge its own integrity.

• 2026-04-10 — 🧠 tools/smart_update.sh — intelligent skill updater. Compares local vs upstream, detects personal customizations (server paths, API keys), only updates safe skills. bash tools/smart_update.sh --apply

• 2026-04-10 — 🏆 Community paper: UAV-CC — first community paper with full PDF archived. UAV change captioning benchmark for IEEE TGRS by @wxx827. Stack: Claude Opus 4.6 + Codex 5.4 xhigh + Cursor. Papers now archived in community_papers/

• 2026-04-08 — 📚 /research-wiki — persistent research knowledge base inspired by Karpathy's LLM Wiki. Accumulates papers, ideas, experiments, and claims across the entire research lifecycle with typed relationships. Wiki-aware hooks in /research-lit (ingest papers), /idea-creator (read wiki + write ideas back), and /result-to-claim (update claim status + trigger re-ideation). Failed ideas become anti-repetition memory. ARIS now learns from its mistakes.

• 2026-04-05 — 🧬 /meta-optimize — outer-loop harness optimization for ARIS. Passively logs skill invocations, tool calls, failures, and parameter overrides via Claude Code hooks. Run /meta-optimize to analyze accumulated usage data and propose SKILL.md improvements — reviewer-gated, user-approved. Inspired by Meta-Harness (Lee et al., 2026). ARIS now optimizes itself.

• 2026-04-04 — 🔧 Codex Plugin deep integration — /codex:rescue now auto-invoked when experiments fail (Workflow 1.5) or LaTeX won't compile (Workflow 3). GPT independently diagnoses the bug before Claude retries — two AI debuggers are better than one. Optional: codex exec powers nightmare review, /codex:rescue powers auto-debug. Setup →

• 2026-04-03 — ☁️ Modal serverless GPU — no GPU? gpu: modal in CLAUDE.md, one command (modal run launcher.py), no SSH, no Docker, auto scale-to-zero. $30/month free tier — enough to try ARIS experiments without any hardware. pip install modal && modal setup and go. Community contribution by @zeyuzhangzyz

• 2026-04-03 — 🎮 Reviewer Difficulty Levels — medium (default, unchanged), hard (reviewer memory + debate protocol), nightmare (GPT reads repo directly via codex exec — Claude can't hide anything). — difficulty: nightmare for maximum stress test before submission

• 2026-03-30 — 🔥 Auto-debug & exhaust-before-surrender — experiment-bridge auto-diagnoses failures (OOM, import, CUDA, NaN) and retries up to 3×. Inspired by PUA

• 2026-03-30 — ☁️ Vast.ai GPU rental — gpu: vast auto-rents cheapest GPU. By @YIHONG-JIN. 🔧 MiniMax M2.7 upgrade by @octo-patch

• 2026-03-27 — 📄 IEEE venue support (9 families). 🔎 Semantic Scholar. By @ypd666

• 2026-03-26 — 📄 Document-based input — RESEARCH_BRIEF.md auto-detect

• 2026-03-24 — 📝 Workflow 4: /rebuttal — 7-phase pipeline, 3 safety gates

• 2026-03-23 — 🔧 /training-check, /result-to-claim, /ablation-planner integrated. 📦 compact mode. By @JingxuanKang & @couragec

• 2026-03-22 — 📋 Templates — input templates for every workflow. 📄 7 venue templates — CVPR, ACL, AAAI, ACM MM added. 🛡️ Anti-hallucination fix — Workflow 2 enforces DBLP → CrossRef → [VERIFY]. 🔗 base repo — clone a GitHub repo as base codebase (— base repo: https://github.com/org/project)

• 2026-03-22 — 🔍 Codex + Gemini review guide — Codex executes, Gemini reviews via local gemini-review MCP bridge. CN

• 2026-03-20 — 🚀 Antigravity adaptation guide — use ARIS skills in Google Antigravity (agent-first IDE). Community contribution by @PeppaPigw

• 2026-03-20 — 🖥️ Trae adaptation guide — use ARIS skills in Trae (ByteDance AI IDE). Community contribution by @Prometheus-cotigo. 🔢 formula-derivation — Community contribution by @Falling-Flower

• 2026-03-19 — 🖼️ paper-poster — Conference poster. Community contribution by @dengzhe-hou

• 2026-03-19 — 🔗 Workflow 1.5 upgraded — /experiment-bridge GPT-5.4 code review. 📊 W&B fix

• 2026-03-18 — 🎤 paper-slides + 🔁 Codex+Claude bridge + 🖱️ Cursor guide + 🤖 Codex CLI skills + 📝 grant-proposal + 🎨 paper-illustration (Gemini) + 📊 CitationClaw

• 2026-03-17 — 🔧 Git code sync + 🆓 ModelScope guide + parameter pass-through

• 2026-03-16 — 🔬 research-refine + experiment-plan — turn vague ideas into problem-anchored proposals with claim-driven experiment roadmaps. Now integrated into Workflow 1 (/idea-discovery). Community contribution by @zjYao36

• 2026-03-16 — 🇨🇳 Alibaba Coding Plan guide — one API key, 4 models (Kimi-K2.5 + Qwen3.5+ + GLM-5 + MiniMax-M2.7), dual-endpoint setup. Community contribution by @tianhao909

• 2026-03-15 — 🔀 Bring your own model! Any OpenAI-compatible API now works as reviewer via llm-chat MCP server. GLM, MiniMax, Kimi, LongCat, DeepSeek all tested — zero Claude or OpenAI API needed

• 2026-03-15 — 🐾 OpenClaw adaptation guide — use ARIS research workflows in OpenClaw without Claude Code slash skills

• 2026-03-15 — 📐 proof-writer — community skill for rigorous theorem proof drafting. 📚 Anti-hallucination citations — /paper-write now fetches real BibTeX from DBLP/CrossRef instead of LLM-generated entries — on by default, zero install

• 2026-03-14 — 📱 Feishu/Lark integration: three modes (off/push/interactive), mobile notifications for experiments, reviews, and checkpoints

• 2026-03-13 — 🛑 Human-in-the-loop: configurable AUTO_PROCEED checkpoints across all workflows. Full autopilot or step-by-step approval

• 2026-03-12 — 🔗 Zotero + Obsidian + local PDFs + arXiv/Scholar: multi-source literature search with cross-model novelty verification

• 2026-03-12 — 🚀 Three end-to-end workflows complete: one prompt → top-venue-style paper. /research-pipeline chains idea discovery → auto review → paper writing autonomously

• 2026-03-12 — 📝 /paper-writing workflow: narrative report → structured outline → figures → LaTeX → compiled PDF → 2-round auto-improvement (4/10 → 8.5/10)

Give ARIS persistent memory across sessions. Papers, ideas, failed experiments — nothing is forgotten:

# In Claude Code:
> /research-wiki init                         # creates research-wiki/ in your project
# That's it. From now on, /research-lit auto-ingests papers, /idea-creator reads
# the wiki before brainstorming (and writes ideas back), /result-to-claim updates
# claim status. Failed ideas become anti-repetition memory for future ideation.

Run these in your normal terminal (not inside Claude Code) to enable passive usage logging:

# One-time setup in your project directory
mkdir -p .claude .aris/meta tools/meta_opt
cp Auto-claude-code-research-in-sleep/templates/claude-hooks/meta_logging.json .claude/settings.json
cp Auto-claude-code-research-in-sleep/tools/meta_opt/*.sh tools/meta_opt/
chmod +x tools/meta_opt/*.sh
# Then start Claude Code — hooks are active immediately
claude

Events are logged to both project-level (.aris/meta/events.jsonl) and global (~/.aris/meta/events.jsonl) logs. After 5+ workflow runs, run /meta-optimize to see data-driven improvement proposals. Use /meta-optimize --global to analyze trends across all your projects.

📝 Templates available! See templates/ for ready-to-use input templates for every workflow — research brief (Workflow 1), experiment plan (Workflow 1.5), narrative report (Workflow 3), paper plan (Workflow 3).

🔎 Optional: DeepXiv progressive retrieval

pip install deepxiv-sdk

Then use /deepxiv directly or opt into it from /research-lit with — sources: deepxiv or — sources: all, deepxiv.

🔎 Optional: Exa AI-powered web search

pip install exa-py
export EXA_API_KEY=your-key-here

Then use /exa-search directly or opt into it from /research-lit with — sources: exa or — sources: all, exa. Covers blogs, docs, news, and research papers with built-in content extraction.

🔎 Optional: Keenable web search (no API key needed)

export KEENABLE_API_KEY=your-key-here   # optional, only raises rate limits

Then use /keenable-search to search the web (title, URL, and page-text snippet per result) or fetch a URL as markdown. Works without a key and needs no extra Python packages.

🔎 Optional: Firecrawl web search and scraping

export FIRECRAWL_API_KEY=your-key-here

Then use /firecrawl-search to search the web with full-page markdown for each result, or to scrape a URL (HTML or PDF) to markdown. No extra Python packages needed.

🗑️ Uninstall: To remove ARIS skills without affecting your own personal skills:

cd Auto-claude-code-research-in-sleep && ls skills/ | xargs -I{} rm -rf ~/.claude/skills/{}

All pipeline behaviors are configurable via inline overrides — append — key: value to any command:

/research-pipeline "your topic" — AUTO_PROCEED: false                          # pause at idea selection gate
/research-pipeline "your topic" — human checkpoint: true                       # pause after each review round to give feedback
/research-pipeline "your topic" — sources: zotero, web                         # only search Zotero + web (skip local PDFs)
/research-pipeline "your topic" — sources: all, deepxiv                        # default sources plus DeepXiv progressive retrieval
/research-pipeline "your topic" — sources: all, exa                            # default sources plus Exa AI-powered web search
/research-pipeline "your topic" — sources: all, gemini                         # default sources plus Gemini discovery
/research-pipeline "your topic" — sources: all, openalex                       # default sources plus OpenAlex citation graph
/research-pipeline "your topic" — arxiv download: true                         # download top arXiv PDFs during literature survey
/research-pipeline "your topic" — difficulty: nightmare                        # maximum adversarial review before submission
/research-pipeline "your topic" — effort: beast                               # all knobs to maximum — top-venue sprint
/research-pipeline "your topic" — effort: beast, reviewer: oracle-pro         # beast + GPT-5.5 Pro reviewer — ultimate mode
/research-pipeline "your topic" — effort: lite                                # quick exploration, save tokens
/research-pipeline "your topic" — effort: max, review_rounds: 3               # max effort but cap review at 3 rounds
/research-pipeline "your topic" — AUTO_PROCEED: false, human checkpoint: true  # combine options
/proof-checker "paper/" — reviewer: oracle-pro                                # Pro-level proof verification

The runtime's sandbox settings provide a configured baseline, while a tool request may also carry sandbox-related overrides. In the legacy compatibility mode, the effective request can therefore differ from the values written in settings.json.

To make the configured policy authoritative, enable strictMode:

{
  "sandbox": {
    "enabled": true,
    "strictMode": true
  }
}

With strictMode: true, the runtime ignores these LLM-supplied overrides: dangerouslyDisableSandbox, namespaceRestrictions, isolateNetwork, filesystemMode, and allowedMounts. The configured sandbox policy remains in effect even when a tool call requests a different value. This is opt-in so existing configurations keep their legacy behavior by default.

Run aris doctor to inspect the currently reported sandbox state. strictMode controls whether tool requests can override the runtime configuration; it does not replace the host operating system's permissions, filesystem protections, or network policy.

Important: ARIS skills pin the reviewer explicitly (model: gpt-6-astra + a per-tier reasoning effort) in every fresh call — your ~/.codex/config.toml no longer silently decides the reviewer. Still set model = "gpt-6-astra" there (recommended): it covers codex-native/mirror sessions and anything that doesn't pin. ultra/max effort needs codex-cli ≥ 0.144.1 + a session restart.

Choose a reviewer in Codex: install the full skills/skills-codex/ pack and select — reviewer: claude-code, antigravity, or grok. See the backend contract for bridge setup and session rules.

The old Claude/Gemini partial overlays are frozen for existing installations; migrate safely to the full pack. The historical Claude and Gemini guides describe those legacy installations.

Want the Codex mirror install chain? Use tools/install_aris_codex.sh for managed project installs and tools/smart_update_codex.sh for copied Codex installs. The Claude scripts remain the mainline entry points for Claude projects.

The base Codex mirror defaults to a fresh Codex reviewer: same-family reviews remain provisional. Other routes require actual model identities and a completed, in-scope review before cross-family acceptance; a backend selection alone is insufficient. Submission and deterministic verification gates still apply.

• 📊 87 composable skills — mix and match, or chain into full pipelines (/idea-discovery, /auto-review-loop, /paper-writing, /research-pipeline). See full catalog →

• 🔍 Literature & novelty — multi-source paper search (Zotero + Obsidian + local PDFs + arXiv/Scholar) + cross-model novelty verification

• 💡 Idea discovery — literature survey → brainstorm 8-12 ideas → novelty check → GPU pilot experiments → ranked report

• 🔄 Auto review loop — 4-round autonomous review, 5/10 → 7.5/10 overnight with 20+ GPU experiments

• 📝 Paper writing — narrative → outline → figures → LaTeX → PDF → auto-review (4/10 → 8.5/10), one command. Anti-hallucination citations via DBLP/CrossRef

• 🤖 Cross-model collaboration — Claude Code executes and GPT-6-Astra reviews; in Copilot CLI, /auto-review-loop uses the native complementary rubber-duck model and verifies the actual cross-family pair from host events. Optional: — reviewer: oracle-pro → GPT-5.5 Pro via Oracle

• 📝 Peer review — review others' papers as a conference reviewer, with structured scoring and meta-review

• 🖥️ Review-driven experiments — when GPT-6-Astra says "run an ablation", Claude auto-writes the script, rsyncs to GPU, runs in screen, collects results, folds back into the paper. Configure server in CLAUDE.md (setup), or rent from Vast.ai with gpu: vast

• 🔀 Flexible models — default Claude × GPT-6-Astra, also supports GLM, MiniMax, Kimi, LongCat, DeepSeek, etc. — no Claude or OpenAI API required

• 🛑 Human-in-the-loop — configurable selection checkpoints. AUTO_PROCEED=true reports the choice and continues in the same turn; false asks for approval. Explicit Feishu interactive gates remain user-controlled

• 📱 Feishu/Lark notifications — three modes: off (default, recommended), push-only (webhook → mobile), interactive (approve/reject in Feishu). Zero impact when off

  Preview: Push cards (group) & Interactive chat (private)

  Push Only — group chat cards (experiment done, checkpoint, error, pipeline complete):

  

  Interactive — private chat with Claude Code (approve/reject, custom instructions):

  

• 📚 Research Wiki — persistent knowledge base across papers/ideas/experiments/claims. Failed ideas become anti-repetition memory — ARIS gets smarter every run. Inspired by Karpathy's LLM Wiki

• 🧩 Extensible — domain-specific skills welcome! Add a SKILL.md and open a PR. See community skills like dse-loop (architecture/EDA)

┌─────────────────────────────────────────────────────────────────┐
│              Idea Discovery & Method Refinement                  │
│                                                                  │
│   /research-lit    /idea-creator    /novelty-check               │
│   (find papers)    (brainstorm)     (verify novelty)             │
│         │               │                │                       │
│         ▼               ▼                ▼                       │
│   ┌──────────┐    ┌──────────┐     ┌──────────┐                │
│   │ Scan     │───▶│ Generate │────▶│ Check if │                │
│   │ local    │    │ 8-12     │     │ idea is  │                │
│   │ papers + │    │ ideas    │     │ novel    │                │
│   │ search   │    │ + rank   │     │          │                │
│   └──────────┘    └──────────┘     └──────────┘                │
│                         │                │                       │
│                         ▼                ▼                       │
│                   ┌──────────┐     ┌──────────┐                │
│                   │ Filter   │────▶│ External │                │
│                   │ by cost, │     │ LLM      │                │
│                   │ novelty  │     │ evaluates│                │
│                   └──────────┘     └──────────┘                │
│                                          │                       │
│                   /research-refine       ▼                       │
│                   (refine method)   ┌──────────┐                │
│                         │          │ Freeze   │                │
│                         ▼          │ problem  │                │
│                   ┌──────────┐     │ anchor + │                │
│                   │ Iterate  │◀───▶│ refine   │                │
│                   │ until    │     │ method   │                │
│                   │ score≥9  │     └──────────┘                │
│                   └──────────┘          │                       │
│                         │               ▼                       │
│                   /experiment-plan  ┌──────────┐                │
│                         │          │ Claim-   │                │
│                         ▼          │ driven   │                │
│                   ┌──────────┐     │ experiment│               │
│                   │ Plan     │────▶│ roadmap  │                │
│                   │ runs     │     └──────────┘                │
│                   └──────────┘                                  │
│                                                                  │
│   Typical flow:                                                  │
│   1. /research-lit "discrete diffusion models"                   │
│   2. /idea-creator "DLLMs post training"                         │
│   3. Review ranked ideas, pick top 2-3                           │
│   4. /novelty-check "top idea" (deep verification)               │
│   5. /research-review "top idea" (critical feedback)             │
│   6. /research-refine "top idea" (problem anchor + method)       │
│   7. /experiment-plan (claim-driven roadmap)                     │
│   8. /run-experiment → /auto-review-loop                         │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│                Workflow 1.5: Experiment Bridge                    │
│                                                                  │
│   EXPERIMENT_PLAN.md                                             │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Claude   │────▶│ GPT-6-Astra  │────▶│ Sanity   │               │
│   │ Code     │     │ xhigh    │     │ Check    │               │
│   │ writes   │     │ reviews  │     │ (1 GPU)  │               │
│   │ code     │     │ code     │     │          │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Collect  │◀────│ Monitor  │◀────│ Deploy   │               │
│   │ results  │     │ progress │     │ to GPUs  │               │
│   │          │     │ (+ W&B)  │     │          │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│         │                                                        │
│         ▼                                                        │
│   Ready for /auto-review-loop                                    │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│                    Auto Review Loop                          │
│                                                              │
│   /research-review          /auto-review-loop                │
│   (single deep review)      (autonomous loop)                │
│         │                         │                          │
│         ▼                         ▼                          │
│   ┌──────────┐   ┌──────────┐   ┌──────────┐               │
│   │ External  │──▶│ Implement│──▶│ Monitor  │──▶ repeat     │
│   │ LLM      │   │ fixes    │   │ results  │    until       │
│   │ reviews  │   │ & run    │   │          │    score ≥ 6   │
│   └──────────┘   │ experiments│  └──────────┘               │
│                   └──────────┘                               │
│                                                              │
│   When reviewer suggests a new method direction:             │
│   /novelty-check — verify idea isn't already published       │
│                                                              │
│   Supporting skills:                                         │
│   /run-experiment    — deploy to local/remote/vast.ai GPU     │
│   /analyze-results   — interpret experiment outputs          │
│   /monitor-experiment — check progress, collect results      │
└─────────────────────────────────────────────────────────────┘

What to pass as argument? A short topic or scope is enough — the skill automatically reads your project's narrative docs (NARRATIVE_REPORT.md), memory files, experiment results, and prior reviews to build the full context for GPT-6-Astra. Examples:

• /auto-review-loop "factorized gap in discrete diffusion LMs" — broad topic, skill finds everything
• /auto-review-loop "focus on Section 3-5, our CRF results are weak" — targeted scope with hints
• /auto-review-loop — also works: skill reads project files and infers the topic

🎮 Reviewer Difficulty — control how adversarial the reviewer is:

/auto-review-loop "topic" — difficulty: nightmare    # GPT reads your code and verifies claims itself

🛡️ Key safety features:

• 🔒 MAX_ROUNDS = 4 — prevents infinite loops; stops early if score threshold is met
• ⏱️ > 4 GPU-hour experiments skipped — won't launch massive jobs; flags them for manual follow-up
• 🧠 Prefer reframing over new experiments — when both can address a weakness, chooses the cheaper path
• 🪞 No hiding weaknesses — explicit rule: "Do NOT hide weaknesses to game a positive score"
• 🔧 Fix before re-review — must actually implement fixes before resubmitting; no empty promises
• 💾 Compact recovery — persists state (REVIEW_STATE.json) after each round. If the context window fills up and auto-compacts mid-loop, the workflow reads the state file and resumes from where it left off — no human intervention needed

┌─────────────────────────────────────────────────────────────┐
│                   Paper Writing Pipeline                      │
│                                                               │
│   /paper-plan      /paper-figure     /paper-write             │
│   (outline)        (plots & tables)  (LaTeX draft)            │
│        │                │                 │                   │
│        ▼                ▼                 ▼                   │
│   ┌──────────┐    ┌──────────┐     ┌──────────┐              │
│   │ Claims-  │───▶│ Generate │────▶│ Section  │──┐           │
│   │ Evidence │    │ figures, │     │ by       │  │           │
│   │ Matrix + │    │ tables,  │     │ section  │  │           │
│   │ Section  │    │ LaTeX    │     │ LaTeX    │  │           │
│   │ Plan     │    │ includes │     │ draft    │  │           │
│   └──────────┘    └──────────┘     └──────────┘  │           │
│        │                                          │           │
│        │         /paper-compile                   │           │
│        │         (build PDF)                      │           │
│        │              │                           │           │
│        ▼              ▼                           ▼           │
│   ┌──────────────────────────────────────────────────┐       │
│   │ NARRATIVE_REPORT.md ──► PAPER_PLAN.md ──► paper/ │       │
│   │    (input)             (outline)      (LaTeX+PDF)│       │
│   └──────────────────────────────────────────────────┘       │
│                                                               │
│   Typical flow:                                               │
│   1. Write NARRATIVE_REPORT.md (from Workflow 2 results)      │
│   2. /paper-plan (claims-evidence matrix + section plan)      │
│   3. /paper-figure (comparison tables, training curves, etc.) │
│   4. /paper-write (section-by-section LaTeX generation)       │
│   5. /paper-compile (build PDF, fix errors, page check)       │
│   6. /auto-paper-improvement-loop (review ×2 + format check)  │
└─────────────────────────────────────────────────────────────┘

Key features:

• 📐 Claims-Evidence Matrix — every claim maps to evidence, every experiment supports a claim
• 📊 Auto figure generation — line plots, bar charts, comparison tables from JSON data
• 🧹 Clean bib — automated filtering removes uncited entries (948→215 lines in testing). Real BibTeX from DBLP/CrossRef instead of LLM-generated entries
• 📄 Flexible sections — 5-8 sections depending on paper type (theory papers often need 7)
• 🔍 GPT-6-Astra review — each step optionally reviewed by external LLM
• ✂️ De-AI polish — removes AI writing patterns (delve, pivotal, landscape...)
• 🎯 Page verification — pdftotext-based precise check that main body fits page limit

⚠️ Figure generation scope: /paper-figure auto-generates data-driven plots (training curves, bar charts, heatmaps) and comparison tables from JSON/CSV. For architecture diagrams and method figures: illustration: gemini (default) uses Claude→Gemini→Nano Banana Pro for publication-quality diagrams; illustration: mermaid generates Mermaid diagrams for free; illustration: false skips AI figures entirely.

Gemini API setup (for illustration: gemini): Get your API key at Google AI Studio, then set it as an environment variable: export GEMINI_API_KEY="your-key". Or add to your shell profile (~/.zshrc / ~/.bashrc). No other dependencies needed.

Tested end-to-end: Generated a 9-page ICLR 2026 theory paper (7 sections, 29 citations, 4 figures, 2 comparison tables) from a single NARRATIVE_REPORT.md — zero compilation errors, zero undefined references.

Score Progression (Real Test — ICLR 2026 theory paper):

Final: 8 pages main body (ICLR limit: 9), 0 overfull hbox, ICLR-compliant. +4.5 points across 3 rounds.

┌─────────────────────────────────────────────────────────────────┐
│                   Workflow 4: Rebuttal                            │
│                                                                  │
│   Reviews arrive                                                 │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Parse &  │────▶│ Strategy │────▶│ Evidence  │               │
│   │ atomize  │     │ plan     │     │ sprint    │               │
│   │ reviews  │     │          │     │ (optional)│               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Finalize │◀────│ GPT-6-Astra  │◀────│ Draft    │               │
│   │ 2 versions│    │ stress   │     │ rebuttal │               │
│   │          │     │ test     │     │          │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│         │                                                        │
│         ▼                                                        │
│   PASTE_READY.txt (strict) + RICH.md (extended)                  │
│         │                                                        │
│         ▼                                                        │
│   Follow-up rounds (delta replies, per-reviewer threads)         │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│              Workflow 7: Proof Orchestrator                     │
│                                                                 │
│   Theorem arrives (new run, or continuation of a prior run)     │
│         │                                                       │
│         ▼                                                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Freeze   │────▶│ Local    │────▶│ Correct- │               │
│   │ target + │     │ proof    │     │ ness     │               │
│   │ evidence │     │ attempt  │     │ audit    │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                         │                │                      │
│                  LOCAL_BLOCKED     ┌──────────┐                │
│                         │          │ Notation │                │
│                         │          │ + struct │──▶ final.md    │
│                         │          │ gates    │                │
│                         │          └──────────┘                │
│                         ▼                                       │
│   ┌───────────────────────────────────────────┐                │
│   │ GPT Pro handoff package                   │                │
│   │ browser-prompt.md · source-manifest.md ·  │                │
│   │ handoff.md — you drive the browser        │                │
│   └───────────────────────────────────────────┘                │
│                         │                                       │
│                         ▼                                       │
│   gpt-pro-output.md → format repair → re-audit → gates → final │
│                                                                 │
│   Optional on request: DeepSeek adversarial audit via llm-chat  │
│   → validated locally → run-local provisional evidence          │
│                                                                 │
│   State: prompts/<run-id>/ — completed runs are append-only;    │
│   a new run reuses only audited claims                          │
└─────────────────────────────────────────────────────────────────┘

Four entity types:

Typed relationships (stored in graph/edges.jsonl):

paper --extends--> paper              idea --inspired_by--> paper
paper --contradicts--> paper          idea --tested_by--> experiment
paper --addresses_gap--> gap          experiment --supports--> claim
paper --supersedes--> paper           experiment --invalidates--> claim

Spiral learning in action:

Round 1: read 15 papers → wiki remembers → idea A → experiment → FAIL
         wiki records: "A fails because OOM at batch>32, loss diverges"

Round 2: /idea-creator reads wiki → sees A failed → generates idea D (avoids A's trap)
         → experiment → PARTIAL SUCCESS
         wiki records: "D works on small models, fails on large"

Round 3: /idea-creator reads wiki → knows A failed + D partial → generates idea F
         (combines D's success with new approach) → experiment → SUCCESS 🎉

Subcommands:

/research-wiki init                              # initialize wiki
/research-wiki ingest "paper title" — arxiv: xxx  # manually add a paper
/research-wiki query "topic"                      # rebuild query_pack.md
/research-wiki update idea:001 — outcome: negative # update entity
/research-wiki lint                               # health check (orphans, contradictions, stale claims)
/research-wiki stats                              # overview (paper/idea/experiment/claim counts)

Setup (one-time, in normal terminal):

mkdir -p .claude .aris/meta tools/meta_opt
cp Auto-claude-code-research-in-sleep/templates/claude-hooks/meta_logging.json .claude/settings.json
cp Auto-claude-code-research-in-sleep/tools/meta_opt/*.sh tools/meta_opt/
chmod +x tools/meta_opt/*.sh
claude   # hooks active immediately

Usage (after 5+ workflow runs):

> /meta-optimize                        # analyze current project
> /meta-optimize "auto-review-loop"     # focus on one skill
> /meta-optimize --global               # analyze trends across ALL projects
> /meta-optimize apply 1                # apply recommended change #1

┌─────────────────────────────────────────────────────────────────┐
│                  Workflow M: Meta-Optimize                        │
│                                                                  │
│   Normal ARIS usage (W1-W4)                                      │
│         │ (hooks log events passively)                           │
│         ▼                                                        │
│   .aris/meta/events.jsonl                                        │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Analyze  │────▶│ Propose  │────▶│ GPT-6-Astra  │               │
│   │ patterns │     │ SKILL.md │     │ reviews  │               │
│   │          │     │ patches  │     │ patch    │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│                                    User approves?                 │
│                                     Yes → Apply                  │
│                                     No  → Skip                   │
└─────────────────────────────────────────────────────────────────┘

What gets optimized (harness components):

If you previously installed via install_aris.sh (which created .claude/skills/aris/ as a single nested symlink) or via smart_update.sh --target-subdir .claude/skills/aris, your slash commands probably weren't being auto-discovered by Claude Code. Migrate to the flat layout:

# Symlink-style legacy install:
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old

# Copy-style legacy install (with possible local edits — chose strategy explicitly):
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old --migrate-copy keep-user
#   → keeps your nested .claude/skills/aris/ copy intact alongside the new flat install
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old --migrate-copy prefer-upstream
#   → archives nested copy to .aris/legacy-copy-backup-<timestamp>/, then flattens

Project-local copy (no symlinks, useful for per-project skill edits):

mkdir -p ~/your-project/.claude/skills
bash ~/aris_repo/tools/smart_update.sh --project ~/your-project --apply
# Default --target-subdir is .claude/skills (flat), which is what Claude Code expects.
# (The old --target-subdir .claude/skills/aris is now deprecated — see migration block above.)

Global install (one copy in your home dir, available to every project):

mkdir -p ~/.claude/skills
cp -r ~/aris_repo/skills/* ~/.claude/skills/
# Update with: bash tools/smart_update.sh --apply

Global install increases the risk of skill name collisions with other globally-installed packs. Use only if you don't mix ARIS with Superpowers / OpenHands / etc. — otherwise prefer the project-local install above.

codex-plugin-cc provides additional Codex capabilities that ARIS auto-detects when installed:

# In Claude Code:
/plugin marketplace add openai/codex-plugin-cc
/plugin install codex@openai-codex
/reload-plugins
/codex:setup

Where ARIS uses the plugin:

All plugin features are optional — if not installed, ARIS falls back to Claude's own diagnosis. The plugin just adds a second pair of eyes.

Note: ARIS's core cross-model review (paper scoring, idea evaluation, rebuttal stress test) still uses Codex MCP, which allows custom prompts. The plugin cannot replace this.

To run the auto-review loop without clicking permission prompts, add to .claude/settings.local.json:

{
  "permissions": {
    "allow": [
      "mcp__codex__codex",
      "mcp__codex__codex-reply",
      "Write",
      "Edit",
      "Skill(auto-review-loop)"
    ]
  }
}

📰 ARIS-Code v0.4.28（2026-09）—— 最新：ARIS_REASONING_EFFORT 在 Anthropic 通道生效（#446），经由会先发 {} 占位符的中转站时工具调用不再失败（#444），Windows / macOS 的系统代理不用导出 HTTPS_PROXY 就生效（#401）。v0.4.27：启动 REPL 后直接退出不再留下空 session 文件，/resume 只列出有消息的会话（#439 后续）。v0.4.26 让 Fable 5.1 成为 fable 别名与 /model 菜单的第一项（默认 executor 仍是 Opus 5）。v0.4.25 是 reviewer 桥接版：codex-cli 0.154 删掉了 codex mcp-server，升级过 codex 的用户从 ARIS-Code 发起的每次 Codex 审稿都会失败；现在审稿走内建 codex exec 桥接——不需要 mcpServers.codex 条目，旧条目在内存里自动迁移，线程记录与 ARIS 的 Python 桥互通。同版还有：/since 重放你上一次输入之后发生的一切（按现场显示折叠，/since full 看完整输出），/resume 带序号列出会话并显示停在哪（#439），Windows 多行粘贴不再逐行提交（#430，待确认），Windows shim 报错带上原生安装命令（#428），内置 skills 升到 83 个、reviewer 为 GPT-6-Astra。头牌特性：v0.4.24 —— Claude 5 模型刷新（默认 Opus 5、Fable 5 计价档、可用性链）和 v0.4.23 —— 输出折叠。收官 24 个 release（v0.4.5 → v0.4.28）；逐版本详情见下。贡献者：@GetIT-Sunday、@Anduin9527、@GO-player-hhy、@Jxy-yxJ、@screw-44、@StevenUST、@opposj、@ShijunLei-cn、@algojogacor、@YukinoshitaLove、@jinliye-2026、@SajimJC、@JasmineLCY。

逐版本详情（v0.4.5 → v0.4.28）

v0.4.28 (2026-09-28) — ARIS_REASONING_EFFORT 在 Anthropic 通道生效(#446):low / medium / high / xhigh / max,主会话和子代理都支持;不设置则请求不变。ARIS_MAX_TOKENS 调高输出上限,effort 高到撞上限时用。settings 里 autoCompactEnabled: false 关闭自动压缩。🐛 #444 经由会先发 {} 占位符的中转站时,工具调用不再报 invalid tool input JSON。🌐 系统代理:Windows / macOS 的系统代理直接生效,不用再导出 HTTPS_PROXY(#401,by @JasmineLCY);想照旧直连就设 NO_PROXY=*。**升级前看一眼:**已经导出过 ARIS_REASONING_EFFORT、系统里配了代理、或 settings 里写过 autoCompactEnabled: false 的,见升级说明。

v0.4.27 (2026-09-19) — 启动 REPL 后直接退出不再留下空的 session 文件;/resume 只列出有消息的会话(#439 后续)。

v0.4.26 (2026-09-16) — Fable 5.1:fable 别名现在指向 claude-fable-5-1,/model 菜单把 Fable 5.1 放在第一位(Fable 5 仍可选);默认 executor 仍是 claude-opus-5。

v0.4.25 (2026-09-16) — reviewer 桥接版。 codex-cli 0.154 删掉了 codex mcp-server,升级过 codex 的用户从 ARIS-Code 发起的每次 Codex 审稿都会失败。🔴 内建 codex exec 桥接:mcp__codex__codex 改走 codex exec,不需要任何注册 —— 不用 mcpServers.codex 条目,老的 codex mcp-server 条目在内存里自动迁移(env、-c 默认、超时、trust 保留),线程记录与 ARIS 的 Python 桥互通,aris doctor 显示实际后端;ARIS_CODEX_BRIDGE=0 回旧路径。顺带修掉一个老 bug:模型从来拿不到 Codex 结果里的 threadId,所以 codex-reply 一直续不上线程。🆕 /since 重放你上一次输入之后发生的一切(按现场显示折叠;/since full 看完整输出;/resume 之后也可用);工具调用 ≥8 次的回合结束时打一行提示(ARIS_TURN_SUMMARY=0 关闭)。🐛 #430(待 Windows 用户确认)多行粘贴不再逐行提交,Ctrl+C 能停住(ARIS_PASTE_BURST=0)。🐛 #439 /resume 无参数列出会话并带 [n] 序号,接受序号 / id 前缀 / 路径,恢复后直接显示停在哪。#428 Windows shim 的报错带上官方原生安装命令。📦 skills 81 → 83(+/proof-orchestrator、/research-implement-feature;教义与系统提示改为 GPT-6-Astra,回退 gpt-5.6-sol → gpt-5.5;32 个 helper + 仓库根 templates 一并打包)。测试:api 35+6 / aris-cli 225 + 4 e2e / runtime 252 / tools 71 / commands 6 全绿;codex-cli 0.154.0 上 codex exec 真机往返通过。Codex MCP(gpt-6-astra):ultra 设计 gate + 每步 xhigh 实现 gate。

v0.4.24 (2026-08-09) — Claude 5 模型刷新(#392):Claude Opus 5 与 Claude Fable 5(Mythos 级旗舰)一等公民支持。显式 --model claude-opus-5 / claude-fable-5 本来在所有平台就能透传使用 —— 这一版让它们进菜单、算对钱。🆕 默认模型 → claude-opus-5(与 Opus 4.8 同为 $5/$25 档),覆盖主会话、子代理与 aris setup;可用性 fallback 升级为有序链:非显式会话在精确的 404 not_found_error 上沿 Opus 5 → Opus 4.8 → Opus 4.7 逐步前进、每步警告一次(显式选择的模型永不静默更换);旧的单跳 latch 在新默认下会把仅有 4.7 权限的账号卡死在 4.8、并让 v0.4.23 setup 存下的配置彻底失去回落 —— 该回归被跨模型审当场抓住,现由端到端 mock-404 链测试锁死。/model 选择器新增 Fable 5 / Opus 5 / Sonnet 5(4.8 / 4.6 / Haiku 仍可选);别名:fable → claude-fable-5(新增)、opus → claude-opus-5、sonnet → claude-sonnet-5。💰 新增 Mythos 级计价档(2026-08 联网核实):fable/mythos = $10/$50(cache write $12.50、read $1)—— 此前 claude-fable-5 不含任何家族子串,落到保守的未知模型兜底档($15/$75),/cost 全项高估 1.5×;Opus 5 本就被现行 Opus 档算对,现加测试钉死。测试:api 41 / aris-cli 213 + 4 e2e / runtime 226 / tools 70 / commands 5 全绿;claude-opus-5、claude-fable-5、fable 别名三发真机冒烟端到端通过。Codex MCP(gpt-5.6-sol xhigh):实现 gate NO-GO(抓到 fallback 链回归 + 定价史实错误)→ 修复后 GO。

v0.4.23 (2026-08-02) — 输出折叠版 —— 修掉真实用户投诉第一名:CLI 会把读到的文档全文 dump 到屏幕(2000 行论文=刷 2000 行)、bash 全量 stdout、grep 全量匹配内容。🧹 工具输出折叠(仅显示层):Read/Grep 显示前 6 行,Bash 每流显示前 4 + 后 4(stderr 保持红色),然后一行暗色 "… (+N more lines — set ARIS_TOOL_OUTPUT_LINES=0 for full output)";保留行截 240 字符(防 minified 单行);session、模型上下文、--output-format json 和 /export 始终保留完整内容。经核实 thinking 本来就不打屏(体感来自上述 dump)—— 新增两个端到端 sentinel 测试锁死 thinking/reasoning 永不落终端。🐛 bash 超时现在真杀进程 —— 此前超时报告了 interrupted 但命令还在跑、副作用事后落地;ARIS_BASH_KILL_ON_TIMEOUT=0 可回旧行为。📦 内置 skills 79→81:/integrity-forensics(Anti-Autoresearch SHA-pin 启动器:证据台账→GPT 审计→确定性裁决→BLOCK/WARN 门)与 /web-debug-search。grep content 模式不再误报 "0 matches";全部本地 mock 测试代理免疫(此前 shell 挂代理会红 15 个测试)。测试:api 41 / aris-cli 212 + 3 e2e / runtime 225 / tools 69 / commands 5,真代理环境下全绿。Codex MCP(gpt-5.6-sol ultra)裁定折叠设计与 scope(cost/压缩包刻意留到 v0.4.24 —— 两项耦合)。

v0.4.22 (2026-07-11) — skills 大同步 + GPT-5.6-Sol 版。📦 bundle 追平主仓 93 个 commit:79 个内置 skill(新增 meta-apply、paper-poster-html —— 新的测量门控 HTML 海报流水线)、28 个 tools helper(+8)、11 篇新 shared-references 规范文档;同步脚本新增 ARIS_SYNC_EXPECT_SHA 钉版本护栏 + 精确清单漂移测试。🎛 Reviewer 控制面升级到新 skills 携带的 GPT-5.6-Sol 双档制:system prompt 现在放行 skills 显式 pin 的 model: gpt-5.6-sol + 每次调用的 effort(旧的"绝不传 model"规则会把深度审从 ultra 静默压到 xhigh)、携带规范的仅-能力型 fallback 链、并在每次 fresh codex 调用上 pin approval-policy: "never" + 显式 sandbox;HTTP LlmReview fallback 默认刻意保持 gpt-5.5(gpt-5.6-sol 在 chat-completions + reasoning_effort 真烟测通过前仅作实验性选项);落地 gpt-5.6 家族计价(sol $5/$30、terra $2.50/$15、luna $1/$6);banner / Reviewer 行 / /reviewer 全部诚实区分 primary 与 fallback。🐛 8 个核实修复:显式 --model 不再被 saved model 静默覆盖(来源全程追踪;4.8→4.7 可用性回落尊重显式选择);saved model 不再跨 provider 泄漏(OpenAI transport 无模型时 fail-fast);--output-format json 绝不弹审批(单 JSON 文档契约恢复);Windows aris login 修好(PKCE 读 /dev/urandom → getrandom)、Windows 命令探测修好(PowerShell 工具此前用 sh 探测自己);codex .cmd shim 诚实分类(setup 不再写下 MCP 起不来的配置);嵌套 config.json 现在会警告而非静默变全默认;NotebookEdit 不再铸重复 cell id。🖥 新增 windows-latest CI job(编译门 + 3 组定向测试)。测试:api 41 / aris-cli 204 + 1 e2e / runtime 223 / tools 69 / commands 5(+54)全绿。Codex MCP(gpt-5.6-sol ultra):5 轮设计 gate(NO-GO ×4 → GO)+ subagent 实现磁盘核实。

v0.4.21 (2026-06-28) — bug-fix 补丁(Codex 对抗式猎杀挖出的 5 个新真用户 bug —— 全部磁盘核实、与 v0.4.20 不重叠;设计 + 实现两道跨模型审)。🐛 头条:OpenAI-compatible 流式把跨网络 chunk 切断的多字节 UTF-8(中文 / emoji)解成 � —— 每个 HTTP chunk 单独 from_utf8_lossy,于是一个 3 字节中文字或 4 字节 emoji 落在 chunk 边界上就两边都坏(对中文用户 + 国产 OpenAI-compatible provider —— Kimi/GLM/MiniMax/DeepSeek/Qwen/豆包 —— 是高频命中)。流式缓冲改为原始字节,只解码完整 SSE 行。还修:saved 的 OpenAI/custom executor 配置不再覆盖 shell 设的 EXECUTOR_PROVIDER(启动"shell 优先"路径有一处没加 gate → 走错 executor / model not found);Anthropic 流在有内容但无终止信号时 clean-EOF 现在硬报错(premature_eof)而非把半截回答存成完整 turn(与 OpenAI #249 guard 对称;stop_reason-only 兼容路径保留,且 ARIS_ALLOW_EOF_WITHOUT_STOP=1 让"合法地从不发终止信号"的代理回到旧行为);grep_search 的 multiline: true 在 content 模式真能跨行匹配了(此前静默返回空);只装在 structuredContent 里的 MCP 工具结果不再被丢弃。测试(CI 模式):api 35 / runtime 212 / tools 67 / aris-cli 181 / commands 5(+21,含 2 个流级集成测试)全绿。Codex MCP(gpt-5.5 xhigh):设计审(NO-GO → 修掉一个 off-by-one 后 GO)→ 实现审(NO-GO → 补流级集成测试后 GO)。(两个潜在候选 —— Anthropic block-index 路由、OpenAI 多行 SSE —— 仍留硬化 pass。)

v0.4.20 (2026-06-19) — bug-fix 补丁：Codex 对抗式排查出的 7 个用户可见 bug，每个放行前审 3 轮（reviewer 在 GO 前抓到一处 redraw 缺口、一处尾随空行、一处 spinner 残尾、一处空行边界）。🐛 头牌（#299）：短 REPL 回复只剩 "✔ Done" —— spinner 用 Save/RestorePosition 画 "⠋ Thinking…"，让流式输出在同一行覆盖它，但 finish 随后清掉了整行，把一条短的单行回复也抹了。现在这一轮若打印过可见文本，REPL 收尾不再清行（Clear(UntilNewLine) 只擦回复之后的 spinner 残尾）。流式多段回复粘连（"para1para2"）—— 每个 chunk 的段落分隔符在流边界被裁掉；markdown 流式渲染器现在用 held-separator 保留分隔符，使流式输出等同一次完整渲染（无悬空空行）。含 CJK/全角内容的 markdown 表格错位 —— 宽度现在按显示单元计（CJK = 2）而非字符数。aris "prompt" / --print 忽略了 aris setup 存的 executor 模型（此前仅 REPL 生效）—— 配了 OpenAI/自定义 executor 的人，请求却把 Anthropic 默认发到了它的 endpoint；一次性与 REPL 两条路径现在共用一个 resolver。Esc 现在真能关掉补全下拉（之前会被立刻重算回来）。glob_search 截断时报告匹配总数（而非封顶的 100，否则模型会以为 1000 个匹配只有 100 个文件）。/model 的自定义菜单读 executor 实际用的环境，而非过期的磁盘配置。测试（CI 模式）：api 32 / runtime 205 / tools 67 / aris-cli 172 / commands 5 全绿；新增 7 个；真机验证（短回复正常显示 + "✔ Done"；段落保留空行）。Codex MCP（gpt-5.5 xhigh）：排查 → 3 轮审（NO-GO → NO-GO → GO）。两个仅潜伏的候选（Anthropic block-index 路由、OpenAI 多行 SSE）推迟到一次加固 pass。

v0.4.19 (2026-06-14) — 诚实度 / guardrails 补丁（主题来自一次 Codex fresh-eyes 审计；健康配置零行为变化）。🔴 MCP 协议版本协商守卫 —— stdio 握手请求 2025-03-26，却从不读 server 协商回来的版本（一个被解析但没用的字段），于是 server 同意了一个 ARIS 不会说的版本也被静默接受，后续 tools/list / tools/call 跑在不兼容协议上、报错晦涩。ARIS 现在把协商版本对一个受支持集合（2025-11-25 / 2025-06-18 / 2025-03-26 / 2024-11-05 —— 这些之间 stdio 分帧一致）校验，遇到不支持的就终止子进程 + 清槽 + 给出清晰的 per-server 报错（aris doctor 会显示）—— 正是 MCP 生命周期规范要求的"版本谈不拢就终止"。请求仍发 2025-03-26（对 codex mcp-server 验证过），健康 server 不受影响 —— 端到端验证：真实 Codex MCP server 在守卫下仍能拉起 + 初始化 + 暴露工具。🧹 小瑕疵：OpenAI 系 subagent 的响亮报错去掉了过期的 "lands in v0.4.18" 字样（现在版本无关 + 可操作，仍不含凭证）；OpenAI 上游错误体现在会被截断（500 字符）+ 凭证脱敏（sk-… key 和 Bearer … token，用子串扫描器抓住误配代理可能反射回来的紧凑 JSON 形态 {"api_key":"sk-…"}）而非原样喷出；system prompt 的 hook 事件摘要现在只数运行时真正执行的 hook（带 command 字符串的 command hook），和解析器对齐。测试（CI 模式）：api 32 / runtime 204 / tools 67 / aris-cli 167 / commands 5 全绿；live smoke 确认真实 Codex MCP server 在守卫下仍能初始化。Codex MCP（gpt-5.5 xhigh）审：design GO → impl NO-GO（漏了紧凑 secret + command-string 严格性）→ 修后 GO。

v0.4.18 (2026-06-14) — 默认模型 → Claude Opus 4.8，附计费修正 + 安全网。这次升级把 DEFAULT_MODEL、opus 别名、模型选择器、aris setup、subagent 默认都移到 claude-opus-4-8 —— 并带可用性 fallback：若账号没有 4.8（API 返回 404 not_found_error），ARIS 本会话自动回退到 claude-opus-4-7，重建 system-prompt 的模型身份以保持自洽（绝不在实际服务 4.7 时还告诉模型它是 4.8），告警一次后重试 —— 主会话（文本 + JSON）和 subagent 都覆盖。它只在那个精确的 404 上触发（绝不在 400/限流/鉴权上），有防循环 latch，文本路径从回合前快照重建，使重试绝不重复 append 用户消息；有 4.8 的账号与单纯升级字节一致。💰 计费已修正（对 Anthropic 公布的价目表核对过；此前高估了 3–5×）：当前 Opus 4.5–4.8 = $5/$25（弃用的 Opus 4/4.1 保持 $15/$75，按词边界切分，使未来的 opus-4-10 不被错分档）；Sonnet 4.x = $3/$15（与通用未知模型 fallback 解耦，后者仍 $15/$75）；Haiku 本就正确。🧹 待办清理：aris setup 选项 10 把 Codex MCP reviewer 钉到 model_reasoning_effort="xhigh"（对新配置确定、独立于 ~/.codex/config.toml；幂等合并绝不覆盖已有条目）；启动时 + aris doctor 的误配提示（#259）针对被静默忽略/放错位置的配置（坏 JSON，或一个多余的 ~/.aris/config.yaml —— 仅 stderr，使 --print/JSON stdout 保持干净）；system prompt 的 hook 摘要现在把"解析了但从不触发"的事件标为 "PARSED ONLY … will NOT run" 而非暗示死 hook 会跑（完整事件展开 —— 真正触发 SessionStart/SessionEnd/… —— 推迟到单独 issue）。测试（CI 模式）：api 32 / runtime 202 / tools 67 / aris-cli 166 / commands 5 全绿；一次 live one-shot smoke 端到端返回 model=claude-opus-4-8。Codex MCP（gpt-5.5 xhigh）审了 design + 两批实现（design REWORK→GO，impl NO-GO→GO，batch-2 GO）。

v0.4.17 (2026-06-13) — MCP 版本。 v0.4.17 之前，settings.json 里的 mcpServers 只是被解析、在 aris doctor 里显示，却什么都不做；现在 ARIS 会拉起每个配置的 stdio server、走 MCP 握手、发现工具，并在 Anthropic + OpenAI 两条 provider 路径上以 mcp__<server>__<tool> 暴露，端到端调度 + 单 server 软降级 + 未受信 MCP 工具的审批门（--allowedTools 现接受 mcp__ 名）。🆕 零 API key 的跨模型 reviewer：aris setup → 选项 10（Codex MCP，ChatGPT 订阅，无需 API key） 把幂等的 mcpServers.codex 写进运行时真正读取的配置文件（原子写 + 备份，trust: true 前显式确认），可选 API reviewer 作 fallback（ARIS_REVIEWER_PROVIDER=codex-mcp + ARIS_REVIEWER_FALLBACK_PROVIDER）；REPL 内 /setup 重建 system prompt + runtime，reviewer 改动无需退出即生效。🔴 假 server 测不出的协议 bug：真机 e2e 对着 codex mcp-server 才暴露——我们的 stdio 传输在用 LSP 式 Content-Length: 分帧，而 MCP 规范（和 codex）用换行分隔的 JSON-RPC；所有 fake-server 测试都过，是因为 fake 也讲同一种错方言。现在写为 NDJSON、读两种都自动识别，并在 initialize 后补发规范要求的 notifications/initialized（顺带用 select 往返修掉 #286 大请求死锁）。Hooks：object 式 Claude Code hook 保留 matcher / timeout / async（锚定正则匹配；每 hook 超时，默认 30s kill = 警告而非拒绝）。收尾：codex codex/event 通知刷屏默认静默（ARIS_MCP_STDERR=inherit 开），system prompt 现告诉模型别给 Codex 传 model 参数（账号默认 = gpt-5.5 + xhigh），Codex-MCP 为主且无 fallback 的 LlmReview 调用返回清晰的 “用 mcp__codex__codex” 提示而非误导性的 OPENAI_API_KEY 报错。沿用 v0.4.16 零回归方法论（24 个新 characterization 测试）。测试（CI 模式）：runtime 199 / aris-cli 165 / tools 67 / api 30 / commands 5 全绿。Codex MCP（gpt-5.5 xhigh）逐 phase 审 17 轮（7 个 NO-GO 全解决）。

v0.4.16 (2026-05-30) — REPL UX + provider 加固,零回归纪律交付:先写 64 个 characterization（golden）测试锁死当前 provider 路由 / 计费 / reviewer / subagent / REPL 行为,再动手改,全程保持绿。关闭 #274：命令历史持久化到 ~/.config/aris/history（0600 权限）,启动自动加载;ARIS_NO_HISTORY 一键关闭;disk-only secret-skip——疑似凭证的行保留在会话内历史但永不落盘。bash 风格 Ctrl+R 反向增量搜索（CJK 显示宽度感知的单行渲染;不改任何现有按键;零新依赖）。安全:OpenAI 系主会话（Kimi / GLM / MiniMax / …）派 subagent 此前会静默扣用户的 Anthropic OAuth/Keychain 凭证,现在改为响亮报错（错误信息不含凭证名）;完整 OpenAI 系 subagent 路由是跨 crate 改动,推迟到 v0.4.17。地基（零行为变化）:3 处字节级相同的词边界匹配器合并为唯一权威 runtime::word_match;新增纯分类器 ProviderFamily（未接线）。测试（CI 模式）:runtime 164 / aris-cli 128 / tools 49 / commands 5 全绿。Codex MCP（gpt-5.5 xhigh）逐 phase 审 + 最终集成审。

v0.4.15 (2026-05-29) — OpenAI-兼容流式健壮性 hotfix。关闭 #249：MiniMax（及其他 OpenAI-compatible provider / 代理）实际不可用,因为 clean-EOF 完成判定把 data: [DONE] 哨兵当成唯一权威完成信号。非空 choices[].finish_reason 才是 Chat Completions spec 定义的终止帧标志,[DONE] 只是部分 compat provider 不发的 transport 约定（MiniMax 发 finish_reason: "stop" 然后直接关连接不发 [DONE]）。clean-EOF 判定现在抽成可单测纯函数 stream_eof_action(...),见到 [DONE] 或 非空 finish_reason 任一即算完成;不在 finish_reason 处提前停读（include_usage 尾随 usage-only chunk 仍消费）;真截断仍硬报错,出输出前 proxy abort 仍重试。配套：OE7 finish_reason 移到 delta guard 前读（只带 finish_reason 无 delta 的终止 choice）；OE2 任何非空 finish_reason 都 flush pending tool；OE4 mid-stream error 信封硬报错不再静默吞；OE3 容忍 data:{...} 冒号后无空格。+5 单测（77→82）把此前零覆盖的 SSE 完成逻辑抽成纯函数。Anthropic SSE 路径未动。Codex MCP（gpt-5.5 xhigh）3 轮（GO-WITH-NITS → GO-WITH-NITS → GO）。

v0.4.14 (2026-05-25) — 安全 + 文档卫生 release，关闭 v0.4.13 codex audit（gpt-5.5 xhigh，6/10 NEEDS-REWORK）最关键的几项。🔴 S9 (P0) system prompt 配置脱敏 — v0.4.14 之前 render_config_section() 把合并后的 settings.json 原样塞进发给 LLM provider 的 system prompt，会泄漏 env、mcpServers.<name>.headers.Authorization Bearer token、hook command env、签名 URL 的 query 参数、apiKey 等字段。新渲染器：白名单顶层字段（model/permissionMode/theme/outputStyle/permissions/sandbox 子树仍走递归 redact）原样输出；敏感 key（apikey/token/secret/password/authorization/headers/env/_KEY/_SECRET/_TOKEN）递归替换成 [REDACTED]；MCP command 替换 <configured> 占位符；MCP url 仅保留 <scheme://host[:port]> origin（scheme 仅 http/https/ws/wss，host 仅 ASCII，port 仅数字，IPv6 走 [...]）；hook command 字符串完全不输出。Regression test 覆盖 9 处 leak 面；URL parser 单独测 7 种 smuggling（含 codex round-3 抓到的 port 位置 secret 注入）。🟡 P9 (P1)：DeepSeek aris --help 指向 aris setup option 7（真正的 anthropic-compat 菜单项），不再印那条 resolver 根本不认的 EXECUTOR_PROVIDER=anthropic-compat env 路径。🟡 M1/M2 (P1) 文档：aris doctor + README + README_CN 在 mcpServers.len() > 0 时打黄色实验性 warning（完整 MCP 工具分发 v0.4.16 落地）。🟢 C11 (P2) 流式 idle timeout — Anthropic MessageStream 和 OpenAI SSE loop 都在 response.chunk().await 外包 tokio::time::timeout（env ARIS_STREAM_IDLE_TIMEOUT_SECS，默认 120，clamp [10, 1800]，0/负数关闭）；关闭"aris 永远卡死无输出"症状（broken proxy 不发 keepalive 时）。Bundle：77 skills（+1 /wiki-enrich，同日 late sync 到 main 7e3ab67 顺带把上游 check_ready.sh awk + grep-c null-match 修复也带进来），54 helpers。Codex MCP 6 轮（NO-GO + 4 → GO-WITH-NITS + 3 → NO-GO + port smuggling → GO → release metadata GO → sync GO）。

v0.4.13 (2026-05-25) — 收尾 release，关闭从 v0.4.10 到 v0.4.12 累积的所有 codex audit P1 + 补长尾 regression test。🟡 v0.4.10 P1.D per-server MCP timeout — mcpServers.<name>.requestTimeoutSecs override > MCP_REQUEST_TIMEOUT_SECS env > 300s default（clamp 1..=1800），让 codex MCP 可以 5 分钟而 fs MCP 5 秒 timeout 共存。🟡 v0.4.10 known limitation 关闭 — McpStdioProcess::request() 跳过 JSON-RPC notification (id 缺失/null) 继续读直到 response。🟢 meta_opt hook 通过 aris init 部署 — tools/meta_opt/{log_event,check_ready}.sh 嵌入 binary，aris init 写 ARIS-namespaced aris-meta-opt-log-event.sh / aris-meta-opt-check-ready.sh 到 ~/.claude/hooks/（codex round-1 #1：永远不覆盖用户已有同名 hook）；settings.json 合并 idempotent + backup 强保证 + tempfile + rename 原子写。🧪 9 个 v0.4.12 targeted regression test 覆盖 sandbox.strictMode (3) + parse strictMode + provider_match pricing + has_word o-series + stream_options 400 + meaningful-content classification + premature-EOF retry truth table（codex round-1 #3 — should_retry_on_premature_eof() 提成纯函数 + 7 行真值表）。Bundle：76 skills，54 helpers（+2 meta_opt 脚本 vs v0.4.12）。Codex 3 轮（NO-GO + 3 → NO-GO + metadata → GO）。

v0.4.12 (2026-05-22) — Bug-fix + 小功能 release。#238 sandbox.strictMode opt-in 配置项；为 true 时 SandboxConfig::resolve_request() 忽略全部 5 个 LLM-supplied override（dangerouslyDisableSandbox、namespaceRestrictions、isolateNetwork、filesystemMode、allowedMounts）—— 关掉 tool-call 静默绕过用户 sandbox 策略的漏洞。aris doctor 加 "Sandbox:" 一行；bash tool schema 文档化 strictMode 语义。#232 auto-review-loop-llm 从老的 deepseek-chat / deepseek-reasoner（2026-07-24 弃用；reasoner reject tool_choice）改成 deepseek-v4-flash / deepseek-v4-pro。v0.4.10 audit P1 follow-up：P1.A Anthropic 流式 retry 改成基于 has_emitted_meaningful_content（只发了 MessageStart 就 EOF 也能 retry）；P1.B supports_reasoning_effort + reviewer 镜像都用 word-boundary 匹配，openai/o3-mini / proxy:o4 走对路径；P1.C stream_options.include_usage:true proxy fallback —— 真的 400 报 unknown field 时去掉这个字段 retry 一次；P2 pricing 用新 provider_match() 让 qwen3.6-plus / kimi-k2.5 走对 tier，同时拒绝 my-kimi-clone 这种 mid-word 误判。Skills 追新（76 skills, 52 helpers）：嵌入 /interview-cheatsheet + /render-html；build.rs ALLOWED_EXTS 加 html；EXCLUDED_SKILL_PREFIXES → starts_with("skills-codex")。CI fetch-depth: 0 + origin/main fetch 让 drift-test ancestor check 真生效。Codex MCP（gpt-5.5 xhigh）4 轮 review。

v0.4.11 (2026-05-18) — Skills bundle 刷新 + sync 基础设施。v0.4.10 binary 嵌入的 skills 已落后 main（56 个 main skills/ commits 中只有 ~6 个被 cherry-pick 进 bundle）；v0.4.11 sync 完整集合 + 落 sync infrastructure 防漂移再扩大。Bundle：65→74 个 user-facing skill，34→49 个 helper resource。新嵌入 10 个 skill：/citation-audit（第四层文献审计：存在性 + metadata + 引用 context）、/experiment-queue（SSH 多 seed 任务队列，含 OOM retry）、/kill-argument（理论论文双线对抗审）、/resubmit-pipeline（W5：纯文本换会议投稿）、/paper-talk（端到端 conference talk pipeline）、/slides-polish（逐页 Codex 排版审）、/overleaf-sync（双向 Overleaf Git-bridge）、/gemini-search + /openalex（更广文献源）、/qzcli（启智 GPU 任务）。46 个已有 SKILL.md 刷新——最关键是 canonical resolver chain 全面铺开（修复真实事故：硬编码 tools/research_wiki.py 让 /research-wiki 空了一周）+ submission assurance gate + external verifier（/paper-writing Phase 6 现在能跑通）。tools/ 9→18：9 个 baseline 刷新（research_wiki.py 从 315 行刷到 767 行含 canonical ingest_paper API）+ 9 个新增（extract_paper_style.py、figure_renderer.py、paper_illustration_image2.py、overleaf_{setup,audit}.sh、verify_wiki_coverage.sh、watchdog.py、experiment_queue/{build_manifest,queue_manager}.py）。新 tools/sync_main_skills.sh 自动化 main → bundle rsync（symlink 前置检测 + codex-mirror prune + SKILLS_SOURCE_COMMIT 钉版本）。crates/runtime/src/cache.rs 新增 3 个 CI drift test 覆盖全部 4 个 resolver layer pattern。/research-lit 和 /gemini-search 的 Gemini MCP 调用改成 model: 'auto-gemini-3'（避免 OAuth-personal 在 capacity 满时 silent downgrade 到 2.5-pro）。CLI runtime 行为不变——codex-audit P1 follow-up 留在 v0.4.12 backlog。Codex MCP（gpt-5.5 xhigh）5 轮交叉评审（REQUEST CHANGES → APPROVE WITH NITS → NO-GO → GO → final GO）。

v0.4.10 (2026-05-17) — 流式 + MCP 可靠性 + 多 provider 计费。C6 Anthropic MessageStream 和 OpenAI SSE 循环都支持 chunk decode 失败 / 早 EOF 时整段重启请求（ARIS_STREAM_RETRY，default 2，clamp 0..=5，仅在尚未输出任何内容时触发——关闭 #228 "error decoding response body" 循环）。M3 MCP stdio 用 tokio::time::timeout 同时包 send + read（default 300s，env MCP_REQUEST_TIMEOUT_SECS clamp 1..=1800）+ response.id ↔ request.id 关联校验 + ensure_server_ready() try_wait() 检测死进程并 respawn + 任何失败路径 kill().await 让下次调用从干净状态开始（关闭 #151 / #172 "Calling codex..." 卡死）。C8/P4 OpenAI 流式请求加 stream_options.include_usage:true + 解析 cached_tokens；Anthropic 流式合并 MessageStart.usage（input/cache）和 MessageDelta.usage（output）。C9 多 provider 计费 registry（15+ 模型，OpenAI cache_read = input × 0.1 修正之前 generic 50% 高估 5×，DeepSeek cache_hit/cache_miss 分层，has_word() boundary matcher 让 provider/<model> slug 走对 tier）。9 个 dead-code warning 修复；aris setup help 文案与实际行为同步。

v0.4.9 (2026-05-17) — 关闭 Codex v0.4.7 audit 三个 cross-cutting 残留（L1 TLS 双栈 / L3 reasoning_cache 错位 / L4 reasoning replay 无 cap）。2 个新 skill 嵌入（/figure-spec + /paper-illustration-image2 含 scripts/ 子目录，新 Layer 0b = $ARIS_CACHE_DIR/skills/<name>/scripts/）；research_wiki.py 提升到 shared tools/（9+ 调用方）；5 个 SKILL.md 迁移到 fallback chain。

v0.4.8 (2026-05-17) — Skill helper 子系统重写。Bundled helper 在 startup 提取到 ~/.config/aris/cache/<version>/；每次 Skill 调用输出 helperReport JSON + 4 层 resolver preamble；/skills export 一并导出 helper；新 integration-contract.md 含 6 个失败策略；8 个 shared helper（arxiv/deepxiv/exa/S2/openalex/save_trace/verify_papers/verify_paper_audits）嵌入；/research-lit + /deepxiv 迁移。另 4 个 bug 修复：gpt-5.5+tools 在 OpenAI 400；Custom reviewer 重启变 gpt-5.5；缺 signature 字段 (#228)；--version Build date 硬编码。

v0.4.7 (2026-05-16) — DashScope Coding Plan 405 修复 (#159) 通过 native-tls 切换 (#225)；所有 reasoning model 的 reasoning_content replay（不只 Kimi）(#226)；600+ 行死代码 + rustyline 移除 + "Claw Code" → "ARIS-Code" 品牌统一。

v0.4.6 (2026-05-14) — 🚨 两个长期静默 bug 修复：PermissionMode::Prompt 因 derived-Ord 顺序错误一直在静默放过所有 tool；system prompt 硬编码 current_date = "2026-03-31" 让 model 把真实数据判为"未来 / prompt injection"。另 Custom OpenAI 兼容 provider（/setup 选项 11）+ dynamic /models 发现（@Anduin9527 #221 + #222）。

v0.4.5 (2026-05-13) — 推理模型一等公民支持：thinking content blocks 全链路（修 #161）+ reasoning_effort='xhigh' 真正发到 GPT-5.5 / o1 / o3 / o4 / DeepSeek-thinking。DeepSeek V4 Pro + Xiaomi MiMo + Qwen 3.6 + Doubao 加入 /setup（选项 7-10）。对象式 hooks 解析器。默认模型升级 Claude Opus 4.7 + GPT-5.5。REPL 输入加固（折行 / Cmd+V 粘贴 / CJK 边界）。新增 GitHub Actions CI workflow。贡献者：@GO-player-hhy (#186)、@Jxy-yxJ (#171)、@GetIT-Sunday (#216 部分)。

更早历史版本

v0.4.4 (2026-04-20) — Setup UX + reviewer 路由修复（修 #158 / #162）| Anthropic + 自定义 URL 不再强制 Bearer | LlmReview 智能 fallback

v0.4.3 (2026-04-17) — 第三方 Anthropic-compat 代理支持（Bedrock 等）| 致谢 @screw-44

v0.4.2 (2026-04-17) — Auto-compaction 修复 | OpenAI-compat 摘要保留 | Shell API key 不再被清

v0.4.1 (2026-04-15) — Plan 模式 + Ctrl+C 协作中断 + 自动重试 (429/5xx) | 多文件 Memory

• 2026-09-28 — 📚 真论文不再被报成幻觉引用（#445、#447、#450；感谢 @ilya-pershin 和 @AfonsoZhang）。arXiv 有时会连续几分钟用 406 拒绝 Python 的 HTTP 客户端，而 curl 能通；verify_papers.py 把这个拒绝当成"查无此文"，有用户在 38 篇真实论文上跑出 47% 的幻觉率。现在 406 会改走 curl，被拒绝（406 / 401 / 403）一律标 verify_pending，不再标 unverified。设了 SEMANTIC_SCHOLAR_API_KEY 的话标题核对会用上它。最近见过可疑的幻觉率？带 --no-cache 重跑一次。同一轮还有：五个 skill 现在真的能调用正文让它调的子 skill（#440，@Jeremy-xuan）；watchdog 并发注册不再互相覆盖（#443，@hiro-nikaitou）；xhigh 按实际写成审稿常规档（#442，@dreamworld2023）。

• 2026-09-16 — 🧩 ARIS 现在是一个 Claude Code 插件（#437，感谢 @white-drizzle）。claude plugin marketplace add wanshuiyin/Auto-claude-code-research-in-sleep → claude plugin install aris@aris → 跑一次 /aris:setup → 重启。setup 会把插件里自带的 Codex 审稿桥接注册好，codex-cli 0.154+ 上开箱即用。插件 skill 输入时带前缀（/aris:idea-discovery），内部互相调用不受影响。Codex CLI 也能把同一个仓库当插件装（codex plugin marketplace add … → codex plugin add aris@aris），拿到的是 Codex 原生镜像。Cursor、Trae、DeepSeek Harness 各走各的路线。

• 2026-09-10 — 🔌 codex-cli 0.154 删掉了 codex mcp-server,codex MCP 要重新注册。 ARIS 所有审阅调用都走这个入口;0.154 起它会打开交互界面,MCP 握手直接失败。ARIS 自带了替身 mcp-servers/codex-exec/server.py:工具名、返回形状一模一样,底下跑 codex exec,skill 一行不改。跑一次:先在你的 ARIS clone 里 git pull(老 clone 里没有这个文件),再 claude mcp remove codex -s user && claude mcp add codex -s user -- python3 "$HOME/aris_repo/mcp-servers/codex-exec/server.py"(写你 clone 的绝对路径),然后重启 Claude Code。新装和已装的分步指引见 快速开始。0.153 上同样能用,升级前就可以换。OpenAI 官方给的替代是 Claude Code 插件,没有 ultra 档、不能按线程续聊,深审 skill 用不了。Cursor / Trae / Antigravity / Copilot CLI 的配置同一个 key,改成 python3 + 这个路径,见各自适配文档。

• 2026-09-07 — 🧠 默认审阅模型换成 gpt-6-astra。 所有钉 gpt-5.6-sol 的审阅调用改钉 gpt-6-astra;两档 effort(七个深审 ultra、其余 xhigh)不变,执行者也不变——你在哪个 agent 里跑 ARIS 就是哪个。账号还没有这个模型?回退链会依次试 gpt-5.6-sol、gpt-5.5(都 xhigh),不用改配置。

• 2026-09-06 — 🧹 安装器不再往每个项目塞 Copilot profile(#431,感谢 @oblivion-1521)。八月起每次安装都会往你的 .github/agents/ 放两个 Copilot 审稿人 profile 的软链接,不管你用不用——Claude Code 和 Codex 用户拿到的是死文件,提交上去还是坏链接。现在只在装了 auto-review-loop 时才部署;--no-agent-profiles 永久关掉(--agent-profiles 撤销)。下次重跑安装会顺手删掉以前生成的链接,你自己写的文件一律不动。

• 2026-09-03 — 📣 论文是发布会,不是工作汇报(规则采自 anti-defensive-writing-Skill,作者 @Adkid-Zephyr,觉得有用就 🌟)。写作契约新增四条:围绕真正的最强优势组织叙事;打不赢的指标不设为比赛;不占优的数字照样留在表里,证据支持时解释为目标差异或权衡,不支持就平实陈述、收窄主张——不写成认输,也不硬编权衡;每个实验必须有论证职责,没有就出主线;摘要引言按问题 → 缺口 → 思路 → 最硬的结果开场,结论不在最后一段突然自我否定。/auto-paper-improvement-loop 按同样标准挑毛病。收录在 Awesome 社区。

• 2026-08-26 — 🧯 两处过度防御残留(#425)。/research-review 是唯一没带范围约束块的审阅 prompt,现在补上了,简报结尾从光秃秃的"往死里挑"变成"撑得住就明说"——敌意立场一字未动。/research-pipeline 不再因为缺 VENUE 死在过夜跑里:找 idea、实验、分析、叙事报告都与 venue 无关,照常跑完——只推迟排版,盖章等 resume。它还一边写着 VENUE = ICLR 默认值一边禁止静默默认;默认值已删。

• 2026-08-26 — ✍️ 论文不再写成忏悔书(#423、#424;多条规则采自 humanize-paper)。claim 按证据配得上的力度直说;"further research is needed" 这类通用免责只住 Limitations;"别提 X"就是 X 不存在——绝不写 "we do not address X";结果按论证排序,不按实验先后。

• 2026-08-26 — 💡 idea 流水线不再因为"有邻居"就杀 idea(#419–#422;来自社区反馈)。ABANDON 必须指名那篇已经包含你结果的论文;同期工作是 race,你定,不是 veto。生成用双模型(gpt-5.6-sol + gpt-5.5)取并集,要的是对重要问题的创造性强攻,不是钻角落堆模块。搜索照样往死里查。

• 2026-08-21 — 🔌 Codex 审稿连不上时,可配 HTTP 兜底(#413;by @TheFlashForge)。默认关;只在能证明 Codex 根本没收到请求时启用——超时不算,那可能花两份钱买两个打架的结论。兜底读你的原始文件,信任比 Codex 更低,绝不更高。

• 2026-08-21 — 🧹 一天合并四个社区修复(#406–#410;by @ZLZLGe 和 @JasmineLCY)。AUTO_PROCEED=true 真的自己往下走了;idea-discovery 的门要见真审稿回执,不认打勾;缓存的 wiki 上下文读之前先扫描;选 Claude 当审稿人的 Codex 用户找回三个论文 skill。

• 2026-08-09 — 🦆 Copilot CLI 宿主下 /auto-review-loop 默认用原生 rubber-duck 审稿(#360,closes #258)。只在 Copilot CLI 会话里启用;审稿证据从宿主事件复验,同族/不明一律 fail-closed。标准 Claude Code + Codex 搭配不受影响。

• 2026-08-09 — 🚧 /idea-discovery 不能再静默跳过阶段(#383,closes #285;by @3mom3)。五个阶段每个都要有记录在案的证据,否则报告写明 BLOCKED,不装完整。

• 2026-08-05 — 🈶 research wiki 的非 ASCII 修好了(#386、#387;由 @LIMMIL7 报告)。cp936 下写的 wiki 换机器读不了,纯中文标题塌成 <年份>_untitled 还被当重复丢掉。已有 UTF-8 wiki 不受影响。

• 2026-08-04 — 🖼️ 上游动态:posterly——/paper-poster-html 的引擎——大幅设计升级(MIT,by @Chenruishuo;今年 ICML 约 50 张海报出自它)。GitHub · Blog。

• 2026-08-03 — 🧭 /proof-orchestrator——工作流 7:带记忆的证明战役(#381;by @shenmuxing,改编自其 EtaSkill)。有状态的 local-first 证明 run,跨 session 延续,卡住时产出可直接粘贴的 GPT Pro 交接包。/proof-checker 仍是投稿门。

• 2026-07-15 — 🔗 双盲引用字段核对(#371)。新 skill /citation-crosscheck:两个 agent 盲审——一个从本地 .bib 读取每条被引条目,一个从网上独立重抓——再由确定性 gate 逐字段 diff(作者集合+顺序、年份、venue、arXiv-id/DOI),输出并排 .xlsx,每条给出 MATCH/MINOR/MISMATCH。与 /citation-audit(context-fit)互补;这个负责字段准确性。

• 2026-07-14 — 🐞 /web-debug-search（Issue #211）。新增聚焦调试/发现的检索流程：搜索 GitHub Issues 与 Discussions，支持精确/归一化错误字符串匹配、版本兼容性追踪和明确的失败处理。所有结果都标记为调试用途，不能作为论文引用证据。

• 2026-07-14 — 🧩 选择性安装 + 全局脚本指针(#366)。81 个 skill 不再"一股脑全装"——四套安装器都支持按组/按 skill 选装(--list-groups / --groups X,Y / --skills X / --exclude Y,或 TTY 下的全屏勾选界面),pipeline 硬依赖自动带全。更新时上游新增的 skill 会逐个确认(--add-new / --skip-new 供脚本化;拒绝的记住、不再重复问)。同时修了全局 copy 安装(~/.claude/skills)找不到 helper 脚本的问题,新增指针文件 ~/.aris/repo。⚠️ 向后兼容:--quiet 全新安装仍是全装;跑一次任意安装器/更新器即可拿到指针文件。选择性安装 →

• 2026-07-12 — 🛡️ 投稿前,你的论文先过一遍审稿人那侧的取证(#357)。新 skill /integrity-forensics:SHA-pin 薄启动器,把 Anti-Autoresearch 那套敌意审稿人能跑的扫描(证据账本、九个审计维度、数值核心、纯规则裁决器)先跑在你自己的论文上。结论进一道 typed gate——flag 能拦下投稿,"没查出问题"只记作"无新阻断"、不算无罪判决;finding 只有带类型、带 hash 的证据、或人签字的 waiver 才能销项(把句子改个措辞不算数,台账会记下来)。/paper-writing 在 submission 档默认就跑(— self_forensics: false 可关;Codex 镜像是 opt-in,且只能跑上游的确定性切片——能报 flag,永远说不出 CLEAN)。⚠️ 首次运行需要联网克隆并校验上游;跑 bash tools/smart_update.sh --apply 拉取更新。

• 2026-07-10 — 🧠 Reviewer 默认换成 GPT-5.6-Sol,深度审计用上新的 ultra 档(#354)。codex-cli 0.144.1 在 xhigh 之上加了 max、ultra;ARIS 审阅默认走 gpt-5.6-sol,七个重量级裁决(/proof-checker、/kill-argument、/research-review、/experiment-audit、/paper-claim-audit、/result-to-claim、/meta-apply)用 ultra,其余保持 xhigh。codex-cli 版本旧或没有这个模型会自动降级(5.6-sol → 5.5,均 xhigh)——永远不低于 xhigh,单纯超时不降级。顺手修了:/result-to-claim 审稿模型连不上时诚实停下,不再自判自己的实验。⚠️ 升级 codex-cli 到 ≥ 0.144.1,重启 session,跑 bash tools/smart_update.sh --apply。

• 2026-07-03 — 🧬 从 Anthropic 的 Claude Science skills 借来三点小改动(#339、#340、#341;Apache-2.0)。ARIS 现在用同一种写法描述 GPU 环境,同一份配置可以用在 SSH 机器、Modal 和集群上,再让一个全新的 agent 按安装说明走一遍来检查。我们也加了一个小工具,用来测试 skill 描述到底能不能让系统选中正确的 skill。最后,图表和写作检查会把"事实是否正确"和"风格是否好看"分开:事实必须过,风格只是建议。⚠️ 运行 bash tools/smart_update.sh --apply 拉取更新。

• 2026-07-02 — 🔁 把 Karpathy 的 LOOPS.md 思路吸收到 ARIS(#333–#337)。Reviewer 现在会先找哪里可能有问题,而不是礼貌地打个分。遇到奇怪的 review 结论时,ARIS 会先让你看保存下来的 reviewer 记录,而不是立刻再问一遍模型。做坏的构建可以按计划重来,不必一直补丁叠补丁;计划、日志和结果会保留。评分可以参考真实的好/坏例子,/meta-optimize 会问哪些东西该删,/paper-writing 会在动笔前先定清楚"写完"的标准。⚠️ 运行 bash tools/smart_update.sh --apply 拉取更新。

• 2026-06-20 — 📚 Research wiki 四层节点全部用确定性写入器 —— 修复"重新生成的 idea 没被记录"(#305、#306、#307、#308)。一位用户踩到真 bug:首次 /idea-creator 记下的 idea,重新生成时不见了 —— 因为 wiki 页面是 freehand(LLM 手写)写的,这种 prose 步骤在"再生成一版"时容易被跳过。现在每层都有专属 research_wiki.py 写入器,与 ingest_paper 并列:add_claim(claim 出生于 /proof-checker)、upsert_idea(/idea-creator)、add_experiment(/result-to-claim),每个都有 drift-check 守护、防止退化成死代码。claim 的 status 现在是严格的证明轴(verified/refuted/unproven/…),实验支持改由 supports/invalidates 边承载(修掉一个共享 validator 会拒绝的潜伏矛盾);Codex-CLI skill 镜像也已同步。无 research-wiki/ 时零行为变化。

• 2026-06-19 — 🛰 通宵跑的 loop 现在能发现自己死了,或者卡住了(#300、#301、#302;运行模式参考了 Deli Chen 的 AutoResearch)。新的 watchdog 会看无人值守的 loop 还在不在更新状态文件,安静太久就写告警;它只报问题,绝不重启任何带裁决性质的 run。另一个 iteration log 会看每轮有没有新发现:连续两轮没新东西就强制换方向,四轮就叫人接手;结果到底够不够好,仍然交给跨模型 jury 判断。

• 2026-06-07 — 🖼️ /paper-poster-html 成为默认海报流水线;旧的 LaTeX /paper-poster 退役。 它把海报做成一个 HTML/CSS 文件,尺寸就是会议真实印刷尺寸,并且先用测量 gate 检查排版和素材,再让内容 reviewer 看,所以审阅时间不用浪费在列没对齐这类问题上。它还带了模板、可复用海报组件和会议 token 包;核心 gate 机制改造自 posterly(MIT,by @Chenruishuo)。⚠️ /paper-poster 现在重定向到 /paper-poster-html;LaTeX 旧流水线只留在 git history 里。

• 2026-05-31 — 🤝 两个社区工具值得看一眼。 Claude Fleet(@tianyilt)是本地只读看板,方便同时盯住很多 Claude Code / Codex 窗口。posterly(@Chenruishuo)把会议海报做成单个 HTML/CSS 文件,再通过 headless Chromium 导出可印刷 PDF,不用 LaTeX。两个都收录在 Awesome 社区。觉得有用就 🌟 一下。

• 2026-05-29 — ⚙️ ultracode 原生约定层 —— 任意运行时档位都能 fan out 拓宽广度，跨模型裁判席始终神圣不可侵犯。三个新 shared-references 文档把广度和裁决解耦：fan-out-pattern.md（skill 用同家族 Claude subagent 生成候选 —— Tier-1 Workflow / Tier-2 Agent / Tier-3 顺序 —— 全部汇入同一个跨模型裁判席），acceptance-gate.md（"loop 可以 DRIVE，不能 ACQUIT" —— 可自判执行完成度，绝不可自判质量/正确性），external-cadence.md（/loop 和 CronCreate 只是 fire-control，绝非裁判席）。已接入 /idea-creator、/research-lit、/proof-checker、/kill-argument（fan-out）+ 16 个 skill（cadence fence/affordance）。另外：清理 48 个 vestigial Agent grant（最小权限 + drift 守卫），修掉 /idea-creator 的同家族 idea 预筛，并校正 /auto-review-loop 的 OR→AND 停止条件矛盾。没有 ultracode 的用户也立刻受益 —— fan-out 退化成顺序执行，最终裁判席不变。

• 2026-05-28 — 📝 首篇 blog 上线：A Survey on Continuous DLM (2026 H1, 6 papers) —— Ruofeng Yang (SJTU) 写的 long-form 双语技术综述，全程通过 ARIS-in-AI-Offer workflow 完成（Claude Opus 4.7 + Codex GPT-5.5 xhigh + Gemini auto-gemini-3 跨模型讨论）。对比 ELF / 字节 Cola-DLM / Flow-Matching 系列：discrete-DLM 的问题、"known-unknown" 连续空间思路、训练 pipeline、架构 / 参数 / shapes、推理 grids + Tab 6/7 数值结果、去噪轨迹、对比 Cola-DLM 的 Field Landscape。单文件自含 HTML（1.7 MB，无 build）—— 展示 /render-html toolchain 能产出的 long-form 研究分析深度。

• 2026-05-26 — 🌐 8 个 workflow 关键节点自动出 HTML view。/idea-discovery、/auto-review-loop、/research-pipeline、/kill-argument、/proof-checker、/paper-claim-audit、/citation-audit、/rebuttal 跑完会自动调 /render-html 把主 MD 工件渲染成单文件 HTML。成本分层：interim view 用 --no-review，audit / reviewer-facing 交付物保留 full Codex render-fidelity gate。默认开（RENDER_HTML = true），每个 skill 可单独 opt-out。失败非阻塞 —— MD 源始终是 canonical。

• 2026-05-26 — 🤝 本周社区 PR 汇 (5 个 merge)。/wiki-enrich (#247 by @hungchun0201) 补全 ingest_paper 留下的论文 TODO 占位 —— Karpathy LLM-wiki 原则，fetch 链 alphaxiv→deepxiv→arXiv。Mirror drift checker + CI (#241 by @VeraPyuyi) 防 main↔mirror 漂移。/research-pipeline Stage 2/3 统一到 /experiment-bridge 委托 (#243 by @ZBigFish) —— 老的 inline 实现本来就是 bridge 的严格子集。Windows PowerShell 安装器对齐 + reparse-chain 内仓守卫 + -FromOld legacy 迁移 + Windows CI matrix (#242 by @VeraPyuyi)。加 manual-review MCP (#246 by @ZBigFish) —— 第三个 reviewer backend — reviewer: manual，零 API 成本跨模型 review（把 prompt 粘贴到任意非 Claude 模型：DeepSeek / Kimi / ChatGPT / Gemini / 本地 llama），跨模型不变量靠双语 UI 警告 + per-session token 认证 + manual MCP 未装时 fail-closed 保护。

• 2026-05-17 — 🐙 GitHub Copilot CLI 适配 —— 原生 SKILL.md + MCP 支持，无需 skill mirror。安装器（install_aris_copilot.sh）+ smart-updater + 13 个 pytest。社区贡献 by @EarendelH（#229，关闭 #214 / #227 / #203）。

• 2026-05-17 — 🛠 Tools-stability roadmap (Phase 1+2+3) 完整收尾（closes #176 / #177 / #178）。社区反馈 install_aris.sh 跑完但 helper script 在用户项目里找不到。Phase 1 —— 10 个 canonical helper 的所有 SKILL.md 调用方现在统一通过 integration-contract.md §2 定义的 3 层链 .aris/tools/ → tools/ → $ARIS_REPO/tools/ 解析（§2 同时定义 5 种 failure policy A/B/C/D1/D2/E）。Phase 2 —— 新增 advisory CI lint 在 PR 扫硬编码 python3 tools/foo.py 模式（仅警告，永不卡 CI）。Phase 3 —— 3 个 single-owner helper（figure-spec、paper-illustration-image2、experiment-queue）迁入对应 SKILL 的 scripts/ 目录，owner SKILL 用 Layer 0 ${CLAUDE_SKILL_DIR}/scripts/ 优先于 canonical chain，原 tools/ 路径保留 os.execv Python 转发 shim。⚠️ 现有用户：无需操作，legacy tools/ 入口现在是转发 shim。如果 2026-04-30 之后没跑过 install_aris.sh，幂等重跑一次即可全部对齐。

• 2026-05-14 — 🩹 /paper-plan + /paper-write 学会 GAP_REPORT.md + <!-- DATA_NEEDED --> 规则 (#217)。当 — style-ref: 启用且用户项目下存在结构性 assets（figures/、results/、NARRATIVE_REPORT.md 等）时，/paper-plan emit Gap Report，把 exemplar 的 section 拓扑 + 密度（从 style_profile.md）对照用户实际 assets，暴露没有证据填充的结构性槽位（如"exemplar 有 3×4 ablation 表，你没有 ablation 数据"）。然后 /paper-write 在 missing 槽位写 <!-- DATA_NEEDED: <Slot ID> — <描述> --> HTML 注释而不是编造内容——PDF 不可见，grep 友好供人审 triage / /experiment-bridge 后续补实验。是对默认"no placeholders"规则的窄 carve-out，只在 GAP_REPORT 列出的 missing 槽位生效。原始想法来自 @zhangpelf。

• 2026-05-14 — ⚙️ 默认 reviewer 模型：gpt-5.4 → gpt-5.5，覆盖 ~30 个 SKILL.md REVIEWER_MODEL 默认值。Codex MCP 自 2026-04-24 起 runtime 就是 gpt-5.5，本次让文档对齐 runtime。⚠️ 行为变化：(a) 之前 run 留下的 .aris/traces/* JSON 不可复现——重跑用 5.5，边界 case 可能给出不同的 WARN/FAIL 判决（reviewer 质量提升，不是回归）。(b) ChatGPT Plus/Pro 月度配额在重度使用下消耗更快。回退：单次调用传 — reviewer-model: gpt-5.4，或在 skill 文件里固定 REVIEWER_MODEL = gpt-5.4。Oracle Pro tier（— reviewer: oracle-pro）走独立路由，不受影响。

• 2026-05-13 — 🔍 tools/verify_papers.py + Pre-Search Verification Protocol —— 给文献类 skill 加反幻觉过滤。新 helper 走 3 层 fallback 验证（arXiv batch API 每次最多 40 个 ID → CrossRef DOI 查询 → Semantic Scholar 模糊标题匹配，默认 0.6 词重叠阈值），每篇 paper 输出 4 态（verified / unverified / verify_pending / error），顶层 verdict 对齐 assurance-contract.md（PASS / WARN / BLOCKED / ERROR）。关键设计点：网络瞬时失败（5xx、超时、429）单独标 verify_pending 且不计入幻觉率，避免网络挂被当成伪造引用。per-project 缓存路径 <project>/.aris/cache/verify_papers.json，30 天 TTL；缓存键优先级 arxiv:{id_去版本号} → doi:{小写} → title:{sha1[:16]}。shared-references/citation-discipline.md 新增 Pre-Search Verification Protocol 小节，明确 search-time vs write-time 分工：本协议是 SEARCH（Step 1）和完整 VERIFY（Step 2）之间的快速过滤器；/citation-audit 和 /paper-claim-audit 仍是 submission 时的硬性 audit gate，没被替代。/research-lit 新增 mandatory Step 1.5: Verify Candidate Papers 调 helper；/idea-creator 和 /novelty-check 各加 1 行 Key Rule 引用，覆盖 landscape 引用和 Closest Prior Work 表格。保留而非静默删除：未验证 paper 留在输出里打 [UNVERIFIED] 标记，让搜索质量问题对用户可见。可选：shell 里 export ARIS_VERIFY_EMAIL=you@institution.edu 进 CrossRef polite-pool 提高速率。最初由 @YiwenZhu77 在 #120 提出——做了干净重写而非直接合 PR（PR 5 周老 + scope creep 到 figure-style）。

• 2026-05-06 — 🎤 /paper-talk workflow + /slides-polish skill —— 端到端 conference talk pipeline。/paper-talk 编排 paper → slide outline → Beamer + PPTX → per-page polish → assurance 审计 → final report（/paper-writing、/paper-poster 的姊妹 workflow）；组合 /paper-slides、/slides-polish，assurance: conference-ready 时再叠 /paper-claim-audit + /citation-audit。/slides-polish 是 post-generation 视觉打磨阶段：per-page Codex 对照 reference PDF 一页一页审 + 一套针对性 python-pptx / Beamer fix pattern（PPTX 字号 1.5-1.8× 缩放保证投影可读、字号 bump 后 text frame resize、banner 真用 tcolorbox 而不是 centered text、italic style 泄漏防御、em-dash 间距、中文 EA font hint 走 PingFang SC、anonymity placeholder 纪律）。Assurance 阶梯 draft / polished（默认）/ conference-ready 与 effort 轴正交——effort: lite, assurance: conference-ready 合法，意为「快流水线 + 每个审计必出 verdict 才能 final」。Phase 4 staging adapter 把 slide 文字 + 讲稿 + 完整 script 物化成合成 paper 目录（.aris/paper-talk/audit-input/sections/*.tex + symlink 真实 .bib / results/ / figures/），让现有 /paper-claim-audit 和 /citation-audit 用它们 paper-shaped 合约审 talk 内容，输出 6 态 JSON verdict（见 shared-references/assurance-contract.md）。

• 2026-05-05 — 🔁 /resubmit-pipeline —— Workflow 5：跨 venue 文本-only 重投流程 (#208)。把已经打磨好的 paper 从一个 venue 移到另一个，硬约束：不跑新实验、不改 bib、不动 framework、不覆盖任何先前 submission 目录。5 阶段：物理隔离 → 5 层匿名检查 → 三审（proof / claim / citation --soft-only）→ /auto-paper-improvement-loop --edit-whitelist 微编辑 + 每轮 diff gate → /kill-argument 对抗 gate → 终编译 + /overleaf-sync 推送。同 PR 一起落地两个前置 skill 升级：/auto-paper-improvement-loop --edit-whitelist <path>（YAML schema，含 allowed_paths / forbidden_paths / forbidden_operations（如 new_cite / new_theorem_env / numerical_claim）/ forbidden_deletions / requires_user_approval_for / max_edits_per_round）和 /citation-audit --soft-only（bib 冻结时把 KEEP/FIX/REPLACE/REMOVE 翻译成文本改写建议；hallucinated 引用走 drop_cite_in_body_only 动作）。Master RESUBMIT_REPORT.json ledger 兼容 shared-references/assurance-contract.md；7 态 verdict 表（含 USER_DECISION runtime 状态）。

• 2026-05-05 — 🗡 /kill-argument —— 理论论文的对抗式 Attack-Adjudication review (#206)。两个新鲜 codex 5.5 + xhigh thread：Thread 1 写senior area chair 会写的最强 200 字 rejection memo；Thread 2 是独立 adjudicator（不是 paper 的辩护人），读当前 paper 把每个攻击点分类为 answered_by_current_text / partially_answered / still_unresolved，带 file:line evidence。输出 KILL_ARGUMENT.{md,json}，detect-only。集成为 /paper-writing 的 Phase 5.6（在 claim-audit 和 citation-audit 之间），同时作为 /auto-paper-improvement-loop Step 5.5 的 canonical 调用——两处都不再内嵌 prompt 模板。assurance: submission 时对理论/scope-heavy paper 强制运行；非理论纯 empirical paper 自动 emit NOT_APPLICABLE。审计 JSON 兼容 verify_paper_audits.sh（完整 schema 见 shared-references/assurance-contract.md，6 态 verdict）。补 score-based review 漏掉的失败模式：每个 local 组件都对（数字对、引用对、定理证）但论文整体还是 oversell 了它真正证明的东西。

• 2026-05-04 — 🪲 /research-wiki 和 8 个调用方 skill 改用 fallback chain 解析 helper (#204)。Bug：跑过 bash tools/install_aris.sh 后 helper 在 .aris/tools/research_wiki.py（symlink），但 skill 写死了 tools/research_wiki.py，调用时 silently 失败——整个 W1 跑完 research-wiki/ 一直是空的。修复：3 层 chain（.aris/tools/ → tools/ → $ARIS_REPO/tools/），canonical pattern 在 shared-references/wiki-helper-resolution.md。手动 cp 到 <project>/tools/research_wiki.py 的临时方案是 chain 第二层，照常 work。⚠️ 已装 ARIS 用户：重跑一次 bash tools/install_aris.sh——同时拿到 helper 的 Python 3.9 ImportError 修复（独立 bug）。

• 2026-05-03 — 🎨 写作类 skill 的 opt-in — style-ref: <source> 参数 (#202)。/paper-{plan,write,writing,illustration,poster,slides}、/grant-proposal、/auto-paper-improvement-loop 接受可选的 — style-ref: <source> 参数，模仿参考论文的结构性风格（section 顺序、theorem/figure 密度、句长节奏、引用风格），但不复制其 prose / claim / 术语。支持的 source：本地 .tex 目录/文件、本地 PDF、arXiv id（2501.12345 或 arxiv:2501.12345）、HTTP/HTTPS URL。Overleaf URL/ID 会被拒绝——先 /overleaf-sync setup <id> 把项目 clone 到本地再传路径。默认关闭；不传参数时所有 8 个 skill 行为完全不变。Reviewer / auditor 子 skill（/proof-checker、/paper-claim-audit、/citation-audit、improvement-loop reviewer）永远拿不到 style ref——跨模型 review 独立性保留。⚠️ 已安装 ARIS 的用户：helper 是新的 tools/extract_paper_style.py，通过 .aris/tools symlink 分发（install_aris.sh Phase 0，#192 引入）。重跑一次 bash tools/install_aris.sh 刷新 symlink 即可拿到 helper。手动 fallback：cp <ARIS-repo>/tools/extract_paper_style.py <你的项目>/tools/。两者都没做的话，writer skill 会 abort 并给清晰错误指向这条 News

• 2026-05-02 — 🪨 社区项目推荐：rosetta by @SyntaxSmith。Node 程序化访问 ChatGPT Pro / gpt-5.5-pro / DeepResearch——Chrome CDP Fetch 拦截 + WebSocket second-leg streaming；自带 MCP server（Claude Code / Codex / Cline）。是 ARIS 用户 — reviewer: oracle-pro 调高 tier reviewer 的另一种实现路径——同样的能力目标（Pro 级 reviewer），不同机制。已收录到社区 Skills & 扩展。觉得有用 🌟 一下！

• 2026-05-02 — 💎🧿 Model & MCP routing 更新。(a) /gemini-search 默认升级到 gemini-3-pro-preview（最强 Gemini 开箱默认）。⚠️ 需要操作：需要 gemini-cli v0.40+（gemini --version 查版本；老版本 npm i -g @google/gemini-cli 升级）。Legacy override：/gemini-search "topic" — model: gemini-2.5-pro。其他 override：gemini-3-flash-preview（更快）、auto-gemini-3（按负载 route）。(b) /idea-discovery Phase 1 现在默认包含 Gemini 文献检索 (#199)——除非用户显式传 — sources:，否则给 /research-lit 自动注入 — sources: all, gemini；没装 gemini-cli 时优雅 skip。(c) Oracle MCP 上游 PR 队列（steipete/oracle/pulls）是用 — reviewer: oracle-pro（尤其 o3-deep-research / gpt-5.5-pro）时开 issue 之前的第一排查点——ARIS 不 vendor Oracle MCP，你跑的是 @steipete/oracle npm 发布版（reviewer-routing.md）

• 2026-05-02 — 🛠️🔗 Tools-infrastructure 迁移启动。(a) install_aris.sh 创建可选 .aris/tools 符号链接 (#192, 关闭 #174)——4 步 tools-stability 迁移（#174 → #176 → #177 → #178）的 Phase 0；幂等，对老用户零影响直到 rerun installer。(b) /experiment-queue 编排路径修复 (#193)——symlink 第一个真实用户；修了 7 个串联 bug，3 轮 Codex MCP gpt-5.5 xhigh review 抓出 cascade。纯 prose + docstring；queue_manager.py Python 逻辑未动。Windows install_aris.ps1 平行更新作为 follow-up

• 2026-05-02 — 🔬 三个 opt-in audit flag 通过 fast-path delegated-agent 工作流落地 (#187, #188, #189)。/citation-audit --uncited 扫出 bib 里没人 \cite{} 的死条目（纯检测）。/proof-checker --deep-fix 给 Phase 1 reviewer prompt 加 repair-grade 修复计划（corrected_statement / patch plan / closure tests + Schur/quadratic-form 代数 sanity）。/proof-checker --restatement-check 加 Phase 3.6 跨位置定理飘移检测（6 类 drift signature）。flag 不传时零行为变化。同期合了两条文档 PR（#190 thread-policy / #191 auto-loop xref）。delegated-agent + maintainer-fixup 模式；Codex MCP gpt-5.5 xhigh review 抓出 6+ 个 blocker

• 2026-05-01 — 🔍 /research-lit 新增 Gemini + OpenAlex 文献源 (#175，社区贡献 @stdAri)。两个 opt-in 源：/gemini-search（AI 驱动的广覆盖检索，走 jamubc/gemini-mcp-tool MCP）+ /openalex（2.5 亿+ 条目开放引用图，免 API key）。— sources: gemini 或 openalex 显式触发；默认 all 不含（老用户零变化）。Maintainer fixup：修正 @google/gemini-cli npm 包名 + 加 try/except ImportError 让缺 requests 时 OpenAlex silent skip

• 2026-04-20 — 🩹 项目级安装重构：扁平布局 + manifest 追踪 — 修一个真 bug：老的嵌套安装（.claude/skills/aris/）让 Claude Code 的 slash command 自动补全发现不了 skill（CC 只扫一层目录）。在此日期之前用过 install_aris.sh 的项目都中招但大多没意识到。新的 install_aris.sh 给每个 skill 单独创建 symlink 到 .claude/skills/<name>，写版本化 manifest 到 .aris/installed-skills.txt，可重入——再跑一次会自动 reconcile 上游的新增/删除。防御性设计：13 条安全规则（不写穿 symlinked 父目录、mutate 前精确 revalidate target、slug 正则、同目录 atomic rename、绝不覆盖真实文件、mkdir 锁跨平台、ADOPT 状态用于崩溃恢复、…）。--force 拆成细粒度 --adopt-existing / --replace-link。迁移路径：--from-old 走老 symlink；--migrate-copy keep-user|prefer-upstream 走老 copy。smart_update.sh --target-subdir .claude/skills/aris 已弃用并重定向到 install_aris.sh。同时修了 cp -r 的 stale-file bug（现在用 rm -rf && cp -r，上游删的文件不再残留）

• 2026-04-19 — 🔗 /overleaf-sync — 本地 ARIS 论文目录与 Overleaf 项目的双向桥接，基于官方 Overleaf Git Bridge（Premium）。让合作者继续在 Overleaf 网页端编辑，本地同时跑 ARIS 审计/改写流水线（/paper-claim-audit、/citation-audit、/auto-paper-improvement-loop）。子命令：setup（一次性，由用户在终端完成，agent 全程不接触 token）/ pull（diff-protocol——自动识别半截草稿、typo、需要重新触发审计的数字/引用改动）/ push（写入共享 Overleaf 状态前必须用户确认）/ status（三方差异诊断）。Token 永远不进入 agent 或任何文件——只在用户终端里输入一次，存进 macOS Keychain，之后 agent 所有操作都免认证

• 2026-04-19 — 📚 /citation-audit — 证据-到-claim 审计栈的第四层也是最后一层（experiment-audit → result-to-claim → paper-claim-audit → citation-audit）。新鲜跨家族 reviewer（gpt-5.4 通过 Codex MCP）配合 web/DBLP/arXiv 实时查找，对每个 \cite{...} 沿三条独立轴进行验证：存在性（论文是否真在所声称的 arXiv ID/DOI/会议）、元数据正确性（作者/年份/会议/标题与权威源一致）、上下文恰当性（被引论文是否真正支持引用处的 claim——这是最具诊断价值的检查）。每条 entry 给出 KEEP / FIX / REPLACE / REMOVE 判决。已自动集成到 Workflow 3 Phase 5.8 作为投稿前的参考文献门控。实证动机：在一次真实投稿 run 中，多篇真实论文被引用在它们实际不支持的语境中，至少一条 entry 的 author 字段是 "Anonymous"——这些都是仅做元数据检查会漏掉的问题

• 2026-04-17 — 🔀 /experiment-queue 集成到 Workflow 1.5 + research-pipeline — experiment-bridge Phase 4 Deploy 阶段按 milestone 任务数自动路由：≤5 jobs → /run-experiment，≥10 jobs 或 phase 依赖 → /experiment-queue（自带 OOM 重试 / stale screen 清理 / wave 切换门控 / 崩溃安全状态）。新增 --- batch: queue 全局强制选项。EXPERIMENT_PLAN.md 里的大型多种子 sweep（如 36 格 N × seed × n_train grid）现在自动用队列调度，无需手动调用

• 2026-04-17 — 🔗 项目级 symlink 安装（解决 #118）— 新推荐默认安装方式。bash tools/install_aris.sh 自动检测平台（Claude Code / Codex CLI），创建 .claude/skills/aris 或 .agents/skills/aris symlink 指向 ARIS 仓库，在 CLAUDE.md / AGENTS.md 添加 <!-- ARIS:BEGIN --> 管理块告知 agent 仅用项目本地 skill，并在 .aris/skill-source.txt 记录安装元数据。解决 skill 命名冲突问题——当 ARIS 与 Superpowers / OpenHands 等社区 skill 包共用全局目录时，agent 会错误调用其他包的 skill 打断 ARIS 工作流。Windows 用户用 install_aris.ps1（基于 junction）。同时 smart_update.sh 新增 --target-subdir 参数支持 Codex .agents/skills/aris 项目级 copy 安装；symlink 安装会被拒绝并提示用 git pull 更新。全局安装继续支持给 power user

• 2026-04-16 — 🎨 /figure-spec — 确定性 JSON→SVG 渲染器正式包装为一级 skill。论文架构图/工作流/流水线/审计级联图的首选默认方案。形状感知边裁剪（矩形/圆/椭圆/菱形）、自环、弯曲边、多行标签含 CJK 宽度估算。矢量输出可编辑、可复现（相同 spec → 相同 SVG）、无外部 API。Workflow 3 Phase 2b 恢复：illustration: figurespec（新默认）/ gemini / mermaid / false——四档作图引擎互补并存

• 2026-04-16 — ⚙️ /experiment-queue — 面向多 seed 多配置 ML 实验的 SSH 任务队列。从真实 36 格 NeurIPS sweep 的痛点反推设计：OOM 感知重试（延迟退避）、stale screen 清理、wave 切换竞争防护、teacher→student 阶段依赖、崩溃安全的调度器（从 JSON 状态恢复）。声明式 grid 自动展开（如 N × seed × n_train → 36 jobs）。conda_hook + gpu_free_threshold_mib 可配置以适应非标准环境。≥10 jobs 时使用；/run-experiment 继续服务单点实验

• 2026-04-15 — 🛡️ 论文写作流水线加固 — 基于真实 NeurIPS run 失败分析的 10 个 patch。REVIEWER_BIAS_GUARD=true：每轮 review 用全新 thread（codex-reply 导致分数从真实 3/10 膨胀到虚假 8/10）。Reviewer Independence Protocol：禁止向 reviewer 传递修复摘要。Step 4.5 定理重述回归测试：捕捉修复轮次中的定理漂移。Step 5.5 Kill Argument Exercise：理论论文最终轮对抗攻防。位置感知 overfull 阻断。/paper-write 新增 Theory Paper Consistency Pass。Bib Hygiene 强制 DBLP/CrossRef 验证。Phase 5.5 Mandatory Final Claim Audit 作为投稿门控。Review Tracing Protocol：完整 prompt/response 对保存到 .aris/traces/，支持 reviewer-independence 审计（review-tracing.md，save_trace.sh）。灵感来自社区贡献 @李傲龍

• 2026-04-15 — 🎨 FigureSpec 渲染器 v2 — 确定性 JSON→SVG 论文作图。形状感知边裁剪（矩形/圆/椭圆/菱形）、自环、弯曲边、多行标签含 CJK 宽度估算、综合输入验证。经 5 轮 Codex review（3/10→7/10）。ARIS 技术报告中的所有架构图和工作流图均由此生成。/paper-illustration 新增 --- mode: vector 模式

• 2026-04-14 — 📋 /paper-claim-audit — 零上下文论文-证据验证。全新 reviewer（无任何先验上下文）逐一比对论文中的每个数字与原始结果文件。捕捉四舍五入膨胀、最优种子挑选、配置不匹配、增量误差、范围过度声明。自动集成到工作流 3（Phase 4.7）。完成三层审计链：/experiment-audit（代码）→ /result-to-claim（科学）→ /paper-claim-audit（报告）。👁️ Visual PDF review 同步加入 improvement loop——reviewer 现在看编译后 PDF，不只是 LaTeX 源码

• 2026-04-13 — 🧿 GPT-5.4 Pro via Oracle — — reviewer: oracle-pro 调用最强推理模型。API 模式（快）或浏览器模式（免费）。支持 /research-review、/auto-review-loop、/experiment-audit、/proof-checker、/rebuttal、/idea-creator、/research-lit。默认仍为 Codex xhigh。未安装 = 零影响。设置 →

• 2026-04-13 — 🔬 /proof-checker — 严格数学证明验证。20 类问题分类、双轴严重度、侧条件检查表（DCT/MCT/Fubini/IFT/...）、反例红队、证明义务台账。自动集成到工作流 3。

• 2026-04-10 — ⚡ Effort Levels — — effort: lite | balanced | max | beast。控制工作强度。Codex reasoning 永远 xhigh。beast = 全部拉满。默认 balanced = 零变化。

• 2026-04-10 — 🔎 DeepXiv 集成 — 渐进式文献检索。— sources: deepxiv。pip install deepxiv-sdk。社区贡献 by @DreamEnding

• 2026-04-10 — 🛡️ /experiment-audit — 跨模型实验诚实度验证。GPT-5.4 直接读你的评估脚本和结果，检查伪造 GT、分数归一化作弊、幽灵结果、范围夸大（#131, #57）。仅警告不阻断。/result-to-claim 自动读取审计结果。新增 experiment-integrity.md 共享规则。执行者不得审判自己的诚实度。

• 2026-04-10 — 🧠 tools/smart_update.sh — 智能技能更新器。对比本地 vs 上游，检测个人定制（服务器路径、API key 等），只更新安全的 skill。bash tools/smart_update.sh --apply

• 2026-04-10 — 🏆 社区论文：UAV-CC — 首篇带完整 PDF 存档的社区论文。无人机变化描述基准，投稿 IEEE TGRS，作者 @wxx827。配置：Claude Opus 4.6 + Codex 5.4 xhigh + Cursor。论文存档于 community_papers/

• 2026-04-08 — 📚 /research-wiki — 持久化研究知识库，灵感来自 Karpathy 的 LLM Wiki。跨研究全生命周期积累论文、想法、实验、claim 及其 typed 关系。Wiki hooks 集成到 /research-lit（论文入库）、/idea-creator（读 wiki + 写回 idea）、/result-to-claim（更新 claim 状态 + 触发重新构思）。失败的 idea 成为防重复记忆。ARIS 现在能从错误中学习。

• 2026-04-05 — 🧬 /meta-optimize — ARIS 外循环 harness 优化。通过 Claude Code hooks 被动记录技能调用、工具执行、失败和参数覆盖。运行 /meta-optimize 分析使用数据，提出 SKILL.md 改进方案——经 reviewer 审核、用户批准。灵感来自 Meta-Harness（Lee et al., 2026）。ARIS 现在可以优化自己。

• 2026-04-04 — 🔧 Codex Plugin 深度集成 — 实验失败（工作流 1.5）或 LaTeX 编译出错（工作流 3）时，自动调用 /codex:rescue 让 GPT 独立诊断 bug，再由 Claude 重试。两个 AI 一起 debug。codex exec 驱动 nightmare review，/codex:rescue 驱动 auto-debug，各司其职

• 2026-04-03 — ☁️ Modal 无服务器 GPU — 没有 GPU？CLAUDE.md 写 gpu: modal，一条命令跑实验，无需 SSH/Docker，跑完自动停止。$30/月免费额度，pip install modal && modal setup 即可体验 ARIS 全流程。社区贡献 by @zeyuzhangzyz

• 2026-04-03 — 🎮 审稿难度等级 — medium（默认，不变）、hard（reviewer memory + 辩论协议）、nightmare（GPT 通过 codex exec 直接读代码仓库，Claude 无法隐藏任何东西）。投顶会前用 — difficulty: nightmare 做极限压测

• 2026-03-27 — 📄 IEEE 模板（9 个 venue 族）+ 🔎 Semantic Scholar。By @ypd666

• 2026-03-26 — 📄 文档输入 — RESEARCH_BRIEF.md 自动检测

• 2026-03-24 — 📝 工作流 4：/rebuttal — 7 阶段，3 道安全门

• 2026-03-23 — 🔧 /training-check、/result-to-claim、/ablation-planner 集成。📦 compact 模式。By @JingxuanKang & @couragec

• 2026-03-22 — 📋 模板 + 📄 7 个会议模板 + 🛡️ 反幻觉修复 + 🔗 base repo

• 2026-03-22 — 🔍 Codex + Gemini 审稿 — Codex 执行，Gemini 审稿

• 2026-03-20 — 🚀 Antigravity 适配。社区贡献 by @PeppaPigw

• 2026-03-20 — 🖥️ Trae 适配。社区贡献 by @Prometheus-cotigo。🔢 formula-derivation。社区贡献 by @Falling-Flower

• 2026-03-19 — 🖼️ paper-poster。社区贡献 by @dengzhe-hou

• 2026-03-19 — 🔗 工作流 1.5 升级 — GPT-5.4 代码审查 + W&B 修正

• 2026-03-18 — 🎤 paper-slides + 🔁 Codex+Claude bridge + 🖱️ Cursor 适配 + 🤖 Codex CLI skills + 📝 grant-proposal + 🎨 paper-illustration + 📊 CitationClaw

• 2026-03-17 — 🔧 Git 代码同步 + 🆓 ModelScope 指南 + 参数透传

给 ARIS 装上持久记忆。论文、idea、失败实验——什么都不忘：

# 在 Claude Code 中：
> /research-wiki init                         # 创建 research-wiki/ 目录
# 搞定。此后 /research-lit 自动入库论文，/idea-creator 读 wiki 再想 idea
# （并把 idea 写回），/result-to-claim 更新 claim 状态。
# 失败的 idea 成为未来构思的防重复记忆。

在普通终端（不是 Claude Code 会话内）运行以下命令启用被动日志：

# 在项目目录下一次性设置
mkdir -p .claude .aris/meta tools/meta_opt
cp Auto-claude-code-research-in-sleep/templates/claude-hooks/meta_logging.json .claude/settings.json
cp Auto-claude-code-research-in-sleep/tools/meta_opt/*.sh tools/meta_opt/
chmod +x tools/meta_opt/*.sh
# 然后启动 Claude Code — hooks 立即生效
claude

事件同时记录到项目级（.aris/meta/events.jsonl）和全局（~/.aris/meta/events.jsonl）日志。累积 5 次以上工作流运行后，运行 /meta-optimize 查看改进建议。使用 /meta-optimize --global 分析跨项目的使用趋势。

📝 模板可用！ 见 templates/ 目录——每个工作流都有现成输入模板：研究简报（工作流 1）、实验计划（工作流 1.5）、研究叙事（工作流 3）、论文大纲（工作流 3）。

🔎 可选：DeepXiv 渐进式论文检索

pip install deepxiv-sdk

安装后可直接使用 /deepxiv，或在 /research-lit 中通过 — sources: deepxiv / — sources: all, deepxiv 显式启用。

🔎 可选：Exa AI 智能网页搜索

pip install exa-py
export EXA_API_KEY=your-key-here

安装后可直接使用 /exa-search，或在 /research-lit 中通过 — sources: exa / — sources: all, exa 显式启用。覆盖博客、文档、新闻和研究论文，并内置内容提取。

🔎 可选：Keenable 网页搜索（无需 API key）

export KEENABLE_API_KEY=your-key-here   # 可选，仅用于提高速率限制

可直接使用 /keenable-search 搜索网页（每条结果含标题、URL 和网页正文片段），或将指定 URL 抓取为 Markdown。无需 key，也无需额外 Python 包。

🔎 可选：Firecrawl 网页搜索与抓取

export FIRECRAWL_API_KEY=your-key-here

安装后可直接使用 /firecrawl-search：搜索网页并为每条结果返回整页 Markdown，或把一个 URL（HTML 或 PDF）抓取成 Markdown。无需额外 Python 依赖。

🗑️ 卸载： 仅删除 ARIS skills，不影响你自己的 skills：

cd Auto-claude-code-research-in-sleep && ls skills/ | xargs -I{} rm -rf ~/.claude/skills/{}

所有流水线行为均可通过内联参数配置——在命令后追加 — key: value：

/research-pipeline "你的课题" — AUTO_PROCEED: false                          # 在 idea 选择关卡暂停
/research-pipeline "你的课题" — human checkpoint: true                       # 每轮 review 后暂停，可给修改意见
/research-pipeline "你的课题" — sources: zotero, web                         # 只搜 Zotero + 网络（跳过本地 PDF）
/research-pipeline "你的课题" — sources: all, deepxiv                        # 默认源 + DeepXiv 渐进式检索
/research-pipeline "你的课题" — sources: all, exa                            # 默认源 + Exa AI 智能网页搜索
/research-pipeline "你的课题" — sources: all, gemini                         # 默认源 + Gemini 智能发现
/research-pipeline "你的课题" — sources: all, openalex                       # 默认源 + OpenAlex 引用图
/research-pipeline "你的课题" — arxiv download: true                         # 文献调研时下载最相关的 arXiv PDF
/research-pipeline "你的课题" — difficulty: nightmare                        # 投顶会前极限压测
/research-pipeline "你的课题" — AUTO_PROCEED: false, human checkpoint: true  # 组合使用

运行时的 sandbox 配置提供一个基线，但 tool request 也可能携带 sandbox 相关 override。在旧版兼容模式下，最终生效的 request 可能与 settings.json 中写入的值不同。

如果希望配置中的策略成为硬约束，可以开启 strictMode：

{
  "sandbox": {
    "enabled": true,
    "strictMode": true
  }
}

当 strictMode: true 时，运行时会忽略 LLM 传入的以下 override：dangerouslyDisableSandbox、namespaceRestrictions、isolateNetwork、filesystemMode 和 allowedMounts。即使 tool call 请求了不同值，配置中的 sandbox 策略仍然生效。该选项默认关闭，以保持已有配置的兼容行为。

可以运行 aris doctor 查看当前报告的 sandbox 状态。strictMode 只控制 tool request 是否能够覆盖运行时配置；它不替代宿主机的权限、文件系统保护或网络策略。

重要： ARIS skill 现在在每个 fresh call 里显式钉住 reviewer（model: gpt-6-astra + 按档位的 reasoning effort）——~/.codex/config.toml 不再静默决定 reviewer。仍建议在其中写 model = "gpt-6-astra"：它覆盖 codex 原生/mirror 会话和任何未钉住的调用。ultra/max 档需要 codex-cli ≥ 0.144.1 并重启 session。

在 Codex 中选择 reviewer： 安装完整 skills/skills-codex/ 包，调用时指定 — reviewer: claude-code、antigravity 或 grok。桥接配置和续接规则见 backend 契约。

旧 Claude/Gemini partial overlays 已冻结，保留已有安装；请按安全迁移说明切换完整包。原 Claude 和 Gemini 指南保留为旧安装资料。

想走 Codex mirror 安装链？ 项目级受管安装用 tools/install_aris_codex.sh，copy 安装更新用 tools/smart_update_codex.sh。Claude 脚本仍然是 Claude 主线入口。

Codex 基础镜像默认使用新的 Codex reviewer，同家族审阅仍为 provisional。其他路由须核对实际模型身份并完成指定范围审阅，才能记录跨家族验收；选择后端本身不代表通过。投稿及确定性验证 gate 继续适用。

• 📊 87 个可组合 skill — 自由混搭，或串联为完整流水线（/idea-discovery、/auto-review-loop、/paper-writing、/research-pipeline）。完整目录 →

• 🔍 文献 & 查新 — 多源论文搜索（Zotero + Obsidian + 本地 PDF + arXiv/Scholar）+ 跨模型查新验证

• 💡 Idea 发现 — 文献调研 → 头脑风暴 8-12 个 idea → 查新 → GPU pilot 实验 → 排名报告

• 🔄 自动 review 循环 — 4 轮自主审稿，一夜从 5/10 提升到 7.5/10，自动跑 20+ 组 GPU 实验

• 📝 论文写作 — 研究叙事 → 大纲 → 图表 → LaTeX → PDF → 自动审稿（4/10 → 8.5/10），一条命令。通过 DBLP/CrossRef 反幻觉引用

• 🤖 跨模型协作 — Claude Code 执行，GPT-6-Astra xhigh 审稿。对抗式而非自我博弈。可选：— reviewer: oracle-pro → GPT-5.5 Pro via Oracle

• 📝 Peer Review — 以审稿人视角审阅他人论文，结构化打分 + meta-review

• 🖥️ 审稿驱动实验 — GPT-6-Astra 说"跑个消融"，Claude 自动写脚本、rsync 到 GPU、screen 启动、收结果、写回论文。CLAUDE.md 里配服务器（配置），或用 gpu: vast 从 Vast.ai 按需租

• 🔀 灵活模型 — 默认 Claude × GPT-6-Astra，也支持 GLM、MiniMax、Kimi、LongCat、DeepSeek 等——无需 Claude 或 OpenAI API

• 🛑 Human-in-the-loop — 关键决策点可配置检查点。AUTO_PROCEED=true 全自动，false 逐步审批

• 📱 飞书通知 — 三种模式：关闭（默认，推荐）、仅推送（webhook → 手机）、双向交互（飞书里审批/回复）。未配置时零影响

  预览：推送卡片（群聊）& 交互对话（私聊）

  仅推送 — 群聊彩色卡片（实验完成、checkpoint、报错、流水线结束）：

  

  双向交互 — 与 Claude Code 私聊（审批/拒绝、自定义指令）：

  

• 📚 Research Wiki — 持久化知识库，跨论文/idea/实验/claim 累积记忆。失败的 idea 成为防重复记忆——ARIS 每跑一次都更聪明。灵感来自 Karpathy 的 LLM Wiki

• 🧩 可扩展 — 欢迎贡献领域专用 skill！添加一个 SKILL.md 即可提 PR。参见社区 skills，如 dse-loop（体系结构/EDA）

1. /research-lit "discrete diffusion models"    ← Zotero→Obsidian→本地→网络，整理全景
   /research-lit "topic" — sources: zotero, web  ← 或指定只搜部分源
   /research-lit "topic" — arxiv download: true   ← 同时下载最相关的 arXiv PDF
2. /idea-creator "DLLMs post training"     ← 自动生成 8-12 个 idea，筛选排序
3. 选 top 2-3 个 idea
4. /novelty-check "top idea"                     ← 查新：有没有人做过？
5. /research-review "top idea"                   ← 让外部 LLM 批判你的想法
6. /research-refine "top idea"                   ← 冻结问题锚点 + 精炼方法
7. /experiment-plan                              ← claim-driven 实验路线图
8. /run-experiment → /auto-review-loop           ← 闭环！

┌─────────────────────────────────────────────────────────────────┐
│                工作流 1.5：实验桥接                                │
│                                                                  │
│   EXPERIMENT_PLAN.md                                             │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ Claude   │────▶│ GPT-6-Astra  │────▶│ Sanity   │               │
│   │ Code     │     │ xhigh    │     │ Check    │               │
│   │ 写代码    │     │ 审查代码  │     │ (1 GPU)  │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ 收集      │◀────│ 监控进度  │◀────│ 部署到    │               │
│   │ 结果      │     │ (+ W&B)  │     │ GPU      │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│         │                                                        │
│         ▼                                                        │
│   准备好进入 /auto-review-loop                                    │
└─────────────────────────────────────────────────────────────────┘

外部 LLM 评审 → Claude Code 实现修复 → /run-experiment 部署 → 收结果 → 再评审 → 循环
                ↑ 需要新方向时自动 /novelty-check 查新

传什么参数？ 简短的主题或范围就够——skill 会自动读取项目中的叙事文档（NARRATIVE_REPORT.md）、memory 文件、实验结果和历史 review，为 GPT-6-Astra 组装完整上下文。示例：

• /auto-review-loop "离散扩散语言模型的 factorized gap" — 宽泛主题，skill 自动搜集
• /auto-review-loop "重点看第 3-5 节，CRF 结果偏弱" — 指定范围 + 提示
• /auto-review-loop — 也行：skill 读项目文件自动推断主题

用法：

> /auto-review-loop 我的 diffusion model 论文

🎮 审稿难度 — 控制 reviewer 的对抗强度：

/auto-review-loop "topic" — difficulty: nightmare    # GPT 自己读你的代码和结果来验证

🛡️ 关键安全机制：

• 🔒 MAX_ROUNDS = 4 — 防止无限循环；达到分数阈值时提前停止
• ⏱️ > 4 GPU-hour 的实验自动跳过 — 不会启动超大实验，标记为"需人工跟进"
• 🧠 优先改叙事而非跑新实验 — 同样能解决问题时，选择成本更低的路径
• 🪞 不隐藏弱点 — 明确规则："不要隐藏弱点来骗高分"
• 🔧 先修后审 — 必须实现修复后再重新 review，不能只承诺修
• 💾 上下文压缩恢复 — 每轮结束后持久化状态到 REVIEW_STATE.json。如果上下文窗口满了触发自动 compact，工作流会从状态文件恢复断点继续——无需人工干预

NARRATIVE_REPORT.md ──► /paper-plan ──► /paper-figure ──► /paper-write ──► /paper-compile
    (研究叙事)          (大纲+矩阵)     (图表+LaTeX)      (逐节LaTeX)      (编译PDF)

典型流程：
1. 写 NARRATIVE_REPORT.md（来自工作流 2 的结果）
2. /paper-plan — 生成 claims-evidence 矩阵 + 分节计划
3. /paper-figure — 生成对比表、训练曲线等图表
4. /paper-write — 逐 section 生成 LaTeX（含 bib 清理、de-AI 打磨）
5. /paper-compile — 编译 PDF、修复错误、页数验证
6. /auto-paper-improvement-loop — 内容审稿 ×2 + 格式合规检查

核心特性：

• 📐 Claims-Evidence 矩阵 — 每个声明映射到证据，每个实验支撑一个声明
• 📊 自动图表生成 — 从 JSON 数据生成折线图、柱状图、对比表
• 🧹 Bib 自动清理 — 过滤未引用条目（实测 948→215 行）。通过 DBLP/CrossRef 获取真实 BibTeX，替代 LLM 生成
• 📄 灵活节数 — 5-8 节按论文类型选择（理论论文常需 7 节）
• 🔍 GPT-6-Astra 审稿 — 每步可选外部 LLM 审查
• ✂️ De-AI 打磨 — 去除 AI 写作痕迹（delve、pivotal、landscape…）
• 🎯 精确页数验证 — 基于 pdftotext 定位 Conclusion 结束位置

⚠️ /paper-figure 能做什么、不能做什么： 能自动生成数据驱动的图表（训练曲线、柱状图、热力图）和 LaTeX 对比表（从 JSON/CSV 数据）。不能生成架构图、流程图、模型示意图、生成样本网格——这些需要手动创建（draw.io、Figma、TikZ 等），放到 figures/ 目录后再跑 /paper-write。一篇典型 ML 论文中，约 60% 的图表可自动生成，约 40% 需手动制作。

端到端实测： 从一份 NARRATIVE_REPORT.md 生成了一篇 9 页 ICLR 2026 理论论文（7 节、29 条引用、4 张图、2 个对比表）——零编译错误、零 undefined reference。

分数变化（实测 — ICLR 2026 理论论文）：

最终：正文 8 页（ICLR 限 9 页），0 个 overfull hbox，格式合规。 3 轮共涨 4.5 分。

┌─────────────────────────────────────────────────────────────────┐
│                   工作流 4：Rebuttal                              │
│                                                                  │
│   审稿意见到达                                                    │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ 解析 +    │────▶│ 策略     │────▶│ 证据     │               │
│   │ 原子化    │     │ 规划     │     │ 补跑     │               │
│   │ 审稿意见  │     │          │     │（可选）  │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ 定稿     │◀────│ GPT-6-Astra  │◀────│ 起草     │               │
│   │ 双版本    │     │ 压力测试 │     │ rebuttal │               │
│   │          │     │          │     │          │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│         │                                                        │
│         ▼                                                        │
│   PASTE_READY.txt（严格字数）+ RICH.md（扩展版）                │
│         │                                                        │
│         ▼                                                        │
│   Follow-up 回合（delta 回复，per-reviewer threads）            │
└─────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────┐
│              Workflow 7: Proof Orchestrator                     │
│                                                                 │
│   定理到达(新开 run,或接续旧 run)                             │
│         │                                                       │
│         ▼                                                       │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ 冻结目标 │────▶│ 本地证明 │────▶│ 正确性   │               │
│   │ + 本地   │     │ 攻坚     │     │ 审计     │               │
│   │ 证据     │     │          │     │          │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                         │                │                      │
│                  LOCAL_BLOCKED     ┌──────────┐                │
│                         │          │ 记号门 + │                │
│                         │          │ 结构门   │──▶ final.md    │
│                         │          │          │                │
│                         │          └──────────┘                │
│                         ▼                                       │
│   ┌───────────────────────────────────────────┐                │
│   │ GPT Pro 交接包                            │                │
│   │ browser-prompt.md · source-manifest.md ·  │                │
│   │ handoff.md —— 浏览器由你来开              │                │
│   └───────────────────────────────────────────┘                │
│                         │                                       │
│                         ▼                                       │
│   gpt-pro-output.md → 格式修复 → 复审 → 两道门 → final.md      │
│                                                                 │
│   可选(按需):DeepSeek 对抗审 via llm-chat                    │
│   → 本地核验 → run 内 provisional 证据                         │
│                                                                 │
│   状态:prompts/<run-id>/ —— 完成的 run 只增不改;              │
│   新 run 只复用审计通过的 claim                                 │
└─────────────────────────────────────────────────────────────────┘

四种实体： 📄 论文、💡 想法、🧪 实验、📋 声明

螺旋上升：

第 1 轮：读 15 篇论文 → idea A → 实验 → 失败 → wiki 记住"A 因为 OOM 失败"
第 2 轮：wiki 知道 A 不行 → idea D（避开 A 的坑）→ 部分成功 → wiki 记住
第 3 轮：综合 A 失败 + D 部分成功 → idea F → 成功 🎉

子命令：

/research-wiki init                               # 初始化
/research-wiki ingest "论文标题" — arxiv: xxx       # 手动添加论文
/research-wiki query "主题"                        # 重建 query_pack.md
/research-wiki lint                                # 健康检查
/research-wiki stats                               # 统计概览

设置（一次性，在普通终端）：

mkdir -p .claude .aris/meta tools/meta_opt
cp Auto-claude-code-research-in-sleep/templates/claude-hooks/meta_logging.json .claude/settings.json
cp Auto-claude-code-research-in-sleep/tools/meta_opt/*.sh tools/meta_opt/
chmod +x tools/meta_opt/*.sh
claude   # hooks 立即生效

使用（累积 5 次以上工作流运行后）：

> /meta-optimize                        # 分析当前项目
> /meta-optimize "auto-review-loop"     # 聚焦单个技能
> /meta-optimize --global               # 分析跨项目的使用趋势
> /meta-optimize apply 1                # 应用推荐的修改 #1

┌─────────────────────────────────────────────────────────────────┐
│                  工作流 M：Meta-Optimize                         │
│                                                                  │
│   正常 ARIS 使用（W1-W4）                                        │
│         │ （hooks 被动记录事件）                                   │
│         ▼                                                        │
│   .aris/meta/events.jsonl                                        │
│         │                                                        │
│         ▼                                                        │
│   ┌──────────┐     ┌──────────┐     ┌──────────┐               │
│   │ 分析模式  │────▶│ 提出      │────▶│ GPT-6-Astra  │               │
│   │          │     │ SKILL.md │     │ 审核      │               │
│   │          │     │ 修改      │     │ patch    │               │
│   └──────────┘     └──────────┘     └──────────┘               │
│                                          │                       │
│                                          ▼                       │
│                                    用户批准？                     │
│                                     是 → 应用                    │
│                                     否 → 跳过                    │
└─────────────────────────────────────────────────────────────────┘

优化对象（harness 组件）： 技能 prompt、默认参数（difficulty、MAX_ROUNDS、threshold）、收敛规则、错误处理模式。

如果你之前用的是 install_aris.sh（创建 .claude/skills/aris/ 嵌套 symlink）或 smart_update.sh --target-subdir .claude/skills/aris（嵌套 copy），那你的 slash command 大概率没被 Claude Code 自动发现。迁移到扁平布局：

# Symlink 老安装：
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old

# Copy 老安装（可能有本地编辑——需要显式选策略）：
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old --migrate-copy keep-user
#   → 保留嵌套 .claude/skills/aris/ 不动，扁平 symlink 装在旁边
bash ~/aris_repo/tools/install_aris.sh ~/your-project --from-old --migrate-copy prefer-upstream
#   → 把嵌套副本归档到 .aris/legacy-copy-backup-<timestamp>/，再扁平化

项目级 copy（不要 symlink，适合需要为单个项目定制 skill 内容）：

mkdir -p ~/your-project/.claude/skills
bash ~/aris_repo/tools/smart_update.sh --project ~/your-project --apply
# 默认 --target-subdir 是 .claude/skills（扁平），这是 Claude Code 期望的布局。
# （老的 --target-subdir .claude/skills/aris 已弃用，见上面的迁移段。）

全局安装（一份 copy 在 home 目录，所有项目可用）：

mkdir -p ~/.claude/skills
cp -r ~/aris_repo/skills/* ~/.claude/skills/
# 更新：bash tools/smart_update.sh --apply

全局安装会增加和其他全局 skill 包名字冲突的风险。只在不混装 ARIS 与 Superpowers / OpenHands 等的情况下使用——否则用上面的项目级安装。

codex-plugin-cc 会提供额外的 Codex 能力；安装后 ARIS 会自动检测并使用：

# 在 Claude Code 中：
/plugin marketplace add openai/codex-plugin-cc
/plugin install codex@openai-codex
/reload-plugins
/codex:setup

ARIS 会在这些地方使用 plugin：

所有 plugin 功能都是可选的；如果没有安装，ARIS 会回退到 Claude 自己的诊断。这个 plugin 只是多加一双眼睛。

注意：ARIS 的核心跨模型审稿（论文评分、idea 评估、rebuttal 压力测试）仍然使用 Codex MCP，因为它支持自定义 prompt。plugin 不能替代这部分能力。

在 .claude/settings.local.json 中添加：

{
  "permissions": {
    "allow": [
      "mcp__codex__codex",
      "mcp__codex__codex-reply",
      "Write",
      "Edit",
      "Skill(auto-review-loop)"
    ]
  }
}