自睡眠自研究系统 是 AI Skill Hub 本期精选MCP工具之一。已获得 9.0k 颗 GitHub Star,综合评分 8.5 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
自睡眠自研究系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
自睡眠自研究系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--------": {
"command": "npx",
"args": ["-y", "auto-claude-code-research-in-sleep"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 自睡眠自研究系统 执行以下任务... Claude: [自动调用 自睡眠自研究系统 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"________": {
"command": "npx",
"args": ["-y", "auto-claude-code-research-in-sleep"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<p align="center"> <a href="https://huggingface.co/papers/2605.03042"> <img src="docs/hf_daily_paper_1.svg" alt="Hugging Face Daily Paper · #1 Paper of the Day" width="360"> </a> </p>
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· 💬 Join Community ·
💡 Use ARIS as a skill-based workflow in Claude Code / Codex CLI / Cursor / Trae / Antigravity / GitHub Copilot CLI / OpenClaw, or get the full experience with the standalone CLI — enjoy any way you like!
🌱 ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go.
🤖 AI agents: Read AGENT_GUIDE.md instead — structured for LLM consumption, not human browsing.
🚀 Beyond 科研 → 任何 "研究":ARIS-Anything 把 ARIS 的五步 loop(plan / draft / 对抗审 / 迭代 / 持久化)推广到非学术的结构化研究——投资尽调 / 法律研究 / 市场研究 / 自驱学习 / 调查新闻 / 工程复盘等。Incoming siblings:🎬 ARIS-Movie(长视频生成 + movie wiki 对抗审)· 📐 ARIS-PRD(产品需求文档)· 🎨 ARIS-Design(设计 brief 对抗评审)· 🏋️ ARIS-Gym(skill 跑分 + OpenAI-Gym-for-research-agents 的 meta 评测层)。
🎯 准备 2026 AI 秋招? → 🌐 ARIS-in-AI-Offer 网页版 · GitHub repo · 中文 README · 23 篇双语 ML / LLM / 多模态 / 生成式 / Agent 面试 cheat sheet 合集——每篇公式推导 + 从零 PyTorch 代码 + 25 高频面试题(L1 必会 / L2 进阶 / L3 顶级 lab),全部由 ARIS 的 /render-html workflow 自动生成。Coming feature:🌐 ARIS-Homepage——给秋招同学自动生成个人主页 / 作品集(CV + 项目 + 论文 bib → 单文件 HTML,跨模型 fact-check venue / 时间 / 模型名)。希望大家秋招的时候轻松一点 🌱
<p align="center"> <a href="https://github.com/wanshuiyin/ARIS-in-AI-Offer"> <img src="https://raw.githubusercontent.com/wanshuiyin/ARIS-in-AI-Offer/main/assets/preview_strip.jpg" alt="ARIS-in-AI-Offer preview — ① Foundations + ② Interview Q&A + ③ From-Scratch Code, three columns from a representative cheat sheet" width="100%"> </a> </p>
📖 Preview from the Diffusion Foundations cheat sheet — every tutorial in ARIS-in-AI-Offer follows the same three-pillar structure (foundations / interview Q&A / runnable code).
🔥 ARIS-Code CLI — 独立安装版 · English | ⬇️ Download
📰 ARIS-Code v0.4.5 → v0.4.11 (2026-05) — Seven-release polish sequence: new providers (DeepSeek V4 Pro / Xiaomi MiMo / Qwen 3.6 / Doubao / Custom OpenAI-compatible / DashScope), first-class reasoning + tool-use (xhigh on the wire, reasoning_content replay, thinking blocks end-to-end), stream + MCP reliability (closes #228 / #151 / #172), multi-provider pricing, skills bundle refresh + sync infrastructure (10 new skills, 46 SKILL.md refreshed, drift CI), and critical bug fixes (PermissionMode silent-allow, hardcoded 2026-03-31 date, Custom reviewer reset, proxy signature field). Per-release detail below. Credits: @GetIT-Sunday, @Anduin9527, @GO-player-hhy, @Jxy-yxJ, @screw-44, @StevenUST. <details><summary>Per-release details (v0.4.5 → v0.4.11)</summary> 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 mainskills/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-wikiwas empty for a week from hardcodedtools/research_wiki.py), submission assurance gate + external verifier (/paper-writingPhase 6 now functions). tools/ goes 9→18: 9 baseline helpers refreshed (research_wiki.py315→767 lines with canonicalingest_paperAPI), 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). Newtools/sync_main_skills.shautomates main → bundle rsync with symlink pre-flight + codex-mirror prune +SKILLS_SOURCE_COMMITpinning. 3 new CI drift tests incrates/runtime/src/cache.rscover all 4 resolver layer patterns. Gemini MCP calls in/research-litand/gemini-searchnow passmodel: '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 AnthropicMessageStream+ 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 defaulttokio::time::timeoutover send+read (overrideMCP_REQUEST_TIMEOUT_SECS, clamp 1..=1800);response.id ↔ request.idcorrelation;ensure_server_ready()try_wait()dead-process respawn;kill().awaiton all failure paths so the next call starts clean (closes #151 / #172 "Calling codex..." stalls). C8/P4 OpenAI streaming requests now sendstream_options.include_usage:true+ parsecached_tokens; Anthropic streaming mergesMessageStart.usage(input/cache) withMessageDelta.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 forprovider/<model>slugs). 9 dead-code warnings cleared;aris setuphelp 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-image2withscripts/subdirs, new Layer 0b =$ARIS_CACHE_DIR/skills/<name>/scripts/);research_wiki.pypromoted to sharedtools/(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 surfaceshelperReportJSON + 4-layer resolver preamble;/skills exportcopies helpers; newintegration-contract.mdwith 6 failure policies; 8 shared helpers (arxiv/deepxiv/exa/S2/openalex/save_trace/verify_papers/verify_paper_audits) bundled;/research-lit+/deepxivmigrated. Plus 4 bug fixes: gpt-5.5+tools 400 on OpenAI; Custom reviewer reset; missingsignaturefield (#228);--versionBuild date hardcoded. v0.4.7 (2026-05-16) — DashScope Coding Plan 405 fixed (#159) vianative-tlsswitch (#225);reasoning_contentreplay for all reasoning models (OpenAI o1/o3/o4 / DeepSeek-R1 etc.), not just Kimi (#226); 600+ lines dead code cleanup +rustylinedep removed + "Claw Code" → "ARIS-Code" rebrand. v0.4.6 (2026-05-14) — 🚨 Two long-standing silent bugs fixed:PermissionMode::Promptsilently allowed every tool (derived-Ordbug); system prompt hardcodedcurrent_date = "2026-03-31"made models reject post-cutoff data as future/prompt-injection. Plus Custom OpenAI-compatible provider (/setupoption 11) with dynamic/modelsdiscovery (@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). </details> <details><summary>Older versions</summary> v0.4.4 (2026-04-20) — Setup UX + reviewer routing fixes (resolves #158, #162) |/setupno 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 foranthropicprovider | 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) —/planstep-by-step planning |/taskspersistent 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 </details>
<img src="docs/aris-code-banner.png" width="600" alt="ARIS-Code CLI">
中文版 README | English
🌙 Let Claude Code do research while you sleep. Wake up to find your paper scored, weaknesses identified, experiments run, and narrative rewritten — autonomously. 🪶 Radically lightweight — zero dependencies, zero lock-in. The entire system is plain Markdown files. No framework to learn, no database to maintain, no Docker to configure, no daemon to babysit. Every skill is a single SKILL.md readable by any LLM — swap Claude Code for Codex CLI, OpenClaw, Cursor, Trae, Antigravity, Copilot CLI, Windsurf, or your own agent and the workflows still work. Fork it, rewrite it, adapt it to your stack. 💡 ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go. 🌱
Custom Claude Code skills for autonomous ML research workflows. These skills orchestrate cross-model collaboration — Claude Code drives the research while an external LLM (via Codex MCP) acts as a critical reviewer. 🔀 Also supports alternative model combinations (Kimi, LongCat, DeepSeek, etc.) — no Claude or OpenAI API required. For example, MiniMax-M2.7 + GLM-5 or GLM-5 + MiniMax-M2.7. 🤖 Codex CLI native — full skill set also available for OpenAI Codex. 🖱️ Cursor — works in Cursor too. 🖥️ Trae — ByteDance AI IDE. 🚀 Antigravity — Google's agent-first IDE. 🐙 Copilot CLI — GitHub's terminal agent (native SKILL.md + MCP). 🆓 Free tier via ModelScope — zero cost, zero lock-in.
💭 Why not self-play with a single model? Using Claude Code subagents or agent teams for both execution and review is technically possible, but tends to fall into local minima — the same model reviewing its own patterns creates blind spots. Think of it like adversarial vs. stochastic bandits: a single model self-reviewing is the stochastic case (predictable reward noise), while cross-model review is adversarial (the reviewer actively probes weaknesses the executor didn't anticipate) — and adversarial bandits are fundamentally harder to game. 💭 Why two models, not more? Two is the minimum needed to break self-play blind spots, and 2-player games converge to Nash equilibrium far more efficiently than n-player ones. Adding more reviewers increases API cost and coordination overhead with diminishing returns — the biggest gain is going from 1→2, not 2→4. Claude Code's strength is fast, fluid execution; Codex (GPT-5.4 xhigh) is slower but more deliberate and rigorous in critique. These complementary styles — speed × rigor — produce better outcomes than either model talking to itself. 🧿 Want the strongest possible reviewer? Add — reviewer: oracle-pro to any skill to route reviews through GPT-5.4 Pro via Oracle MCP. Pro-level reasoning for proof verification, experiment auditing, and final stress tests. Works with API key or free browser mode. Setup →
<a id="contents"></a>
- 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 + ` discipline** ([#217](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/issues/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 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. <details> <summary>Earlier updates (2026-03-12 — 2026-05-14, 63 entries)</summary>
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.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)./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./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./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./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.— 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.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!/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)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/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/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/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 mergeskills/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/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)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— 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.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)/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/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/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 invocationbash 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 ` 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/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/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-hocREVIEWER_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--- mode: vector for /paper-illustration skill/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— 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 →/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— 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 →— sources: deepxiv or — sources: all, deepxiv. Staged reading: search → brief → head → section. pip install deepxiv-sdk to enable. Community contribution by @DreamEnding/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.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 --applycommunity_papers//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./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./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 →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 @zeyuzhangzyzmedium (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 submissiongpu: vast auto-rents cheapest GPU. By @YIHONG-JIN. 🔧 MiniMax M2.7 upgrade by @octo-patchRESEARCH_BRIEF.md auto-detect/rebuttal — 7-phase pipeline, 3 safety gates/training-check, /result-to-claim, /ablation-planner integrated. 📦 compact mode. By @JingxuanKang & @couragecbase repo — clone a GitHub repo as base codebase (— base repo: https://github.com/org/project)gemini-review MCP bridge. CNformula-derivation — Community contribution by @Falling-Flowerpaper-poster — Conference poster. Community contribution by @dengzhe-hou/experiment-bridge GPT-5.4 code review. 📊 W&B fixpaper-slides + 🔁 Codex+Claude bridge + 🖱️ Cursor guide + 🤖 Codex CLI skills + 📝 grant-proposal + 🎨 paper-illustration (Gemini) + 📊 CitationClawresearch-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活跃开源项目,9k星体现社区认可。MCP框架设计先进,Markdown技能易扩展,是AI自动化研究的创新工具。
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| 原始名称 | Auto-claude-code-research-in-sleep |
| 原始描述 | 开源MCP工具:ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomo。⭐9.0k · Python |
| Topics | 自主智能体代码研究MCP工具自动化Claude扩展 |
| GitHub | https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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