Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".

Auto Review Loop (Generic LLM): Autonomous Research Improvement 🔒 Do not wrap this skill in /loop , /schedule , or CronCreate . Like /auto review loop , it already loops internally (review → fix → re review), feeding each round's prior round summary into the next review prompt (the backend is a stateless per round API/MCP call, not a shared thread). An external timer re enters from the top each tick, dropping that accumulated context and firing the verdict on wall clock time instead of on artifact change — zero new signal, full token cost. Schedule the external wait that precedes it , not the verdict. See [ shared references/external cadence.md ](../shared references/external cadence.md). Autonomously iterate: review → implement fixes → re review, until the external reviewer gives a positive assessment or MAX ROUNDS is reached. Context: $ARGUMENTS Constants MAX ROUNDS = 4 POSITIVE THRESHOLD: score = 6/10 AND verdict ∈ {"ready", "almost"} — both must hold, matching the operative STOP check below. Verdict vocabulary is {"ready", "almost", "not ready"}. (Earlier wording used or and a stale verdict set; the AND form is authoritative.) REVIEW DOC: review stage/AUTO REVIEW.md (cumulative log) (fall back to ./AUTO REVIEW.md for legacy projects) LLM Configuration This skill uses any OpenAI compatible API for external review via the llm chat MCP server. Configuration via MCP Server (Recommended) Add to ~/.claude/settings.json : Supported Providers Provider LLM BASE URL LLM MODEL OpenAI https://api.openai.com/v1 gpt 4o , o3 DeepSeek https://api.deepseek.com/v1 deepseek chat , deepseek reasoner MiniMax https://api.minimax.io/v1 MiniMax M3 Kimi (Moonshot) https://api.moonshot.cn/v1 moonshot v1 8k , moonshot v1 32k ZhiPu (GLM) https://open.bigmodel.cn/api/paas/v4 glm 4 , glm 4 plus SiliconFlow https://api.siliconflow.cn/v1 Qwen/Qwen2.5 72B Instruct 阿里云百炼 https://dashscope.aliyuncs.com/compatible mode/v1 qwen max 零一万物 https://api.lingyiwanwu.com/v1 yi large API Call Method Primary: MCP Tool Fallback: curl State Persistence (Compact Recovery) Persist state to review stage/REVIEW STATE.json after each round: Write this file at the end of every Phase E (after documenting the round). On completion , set "status": "completed" . Workflow Initialization 1. Check review stage/REVIEW STATE.json for recovery (fall back to ./REVIEW STATE.json if not found — legacy path) 2. Read project context and prior reviews 3. Initialize round counter Loop (up to MAX ROUNDS) Phase A: Review If MCP available: If MCP NOT available: Phase B: Parse Assessment CRITICAL: Save the FULL raw response verbatim. Then extract: Score (numeric 1 10) Verdict ("ready" / "almost" / "not ready") Action items (ranked list of fixes) STOP : If score = 6 AND verdict ∈ {"ready", "almost"} (exact — "not ready" does NOT qualify) Phase C: Implement Fixes Priority: metric additions reframing new experiments Phase D: Wait for Results Monitor remote experiments Phase E: Document Round Append to review stage/AUTO REVIEW.md : Write review stage/REVIEW STATE.json with current state. Termination 1. Set review stage/REVIEW STATE.json status to "completed" 2. Write final summary Key Rules Large file handling : If the Write tool fails due to file size, immediately retry using Bash ( cat << 'EOF' file ) to write in chunks. Do NOT ask the user for permission — just do it silently. Anti hallucination citations : When adding references, NEVER fabricate BibTeX. Use DBLP → CrossRef → [VERIFY] chain. Do NOT generate BibTeX from memory. Be honest about weaknesses Implement fixes BEFORE re reviewing Document everything Include previous context in round 2+ prompts Prefer MCP tool over curl when available Prompt Template for Round 2+ Output Protocols Follow these shared protocols for all output files: [Output Versioning Protocol](../shared references/output versioning.md) — write timestamped file first, then copy to fixed name [Output Manifest Protocol](../shared references/output manifest.md) — log every output to MANIFEST.md [Output Language Protocol](../shared references/output language.md) — respect the project's language setting

auto-review-loop-llm