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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".
npx skill4agent add wanshuiyin/auto-claude-code-research-in-sleep auto-review-loop-llmAUTO_REVIEW.mdllm-chat~/.claude/settings.json{
"mcpServers": {
"llm-chat": {
"command": "/usr/bin/python3",
"args": ["/Users/yourname/.claude/mcp-servers/llm-chat/server.py"],
"env": {
"LLM_API_KEY": "your-api-key",
"LLM_BASE_URL": "https://api.deepseek.com/v1",
"LLM_MODEL": "deepseek-chat"
}
}
}
}| Provider | LLM_BASE_URL | LLM_MODEL |
|---|---|---|
| OpenAI | | |
| DeepSeek | | |
| MiniMax | | |
| Kimi (Moonshot) | | |
| ZhiPu (GLM) | | |
| SiliconFlow | | |
| 阿里云百炼 | | |
| 零一万物 | | |
mcp__llm-chat__chat:
prompt: |
[Review prompt content]
model: "deepseek-chat"
system: "You are a senior ML reviewer..."curl -s "${LLM_BASE_URL}/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${LLM_API_KEY}" \
-d '{
"model": "${LLM_MODEL}",
"messages": [
{"role": "system", "content": "You are a senior ML reviewer..."},
{"role": "user", "content": "[review prompt]"}
],
"max_tokens": 4096
}'REVIEW_STATE.json{
"round": 2,
"status": "in_progress",
"last_score": 5.0,
"last_verdict": "not ready",
"pending_experiments": [],
"timestamp": "2026-03-15T10:00:00"
}"status": "completed"REVIEW_STATE.jsonmcp__llm-chat__chat:
system: "You are a senior ML reviewer (NeurIPS/ICML level)."
prompt: |
[Round N/MAX_ROUNDS of autonomous review loop]
[Full research context: claims, methods, results, known weaknesses]
[Changes since last round, if any]
1. Score this work 1-10 for a top venue
2. List remaining critical weaknesses (ranked by severity)
3. For each weakness, specify the MINIMUM fix
4. State clearly: is this READY for submission? Yes/No/Almost
Be brutally honest. If the work is ready, say so clearly.curl -s "${LLM_BASE_URL}/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${LLM_API_KEY}" \
-d '{
"model": "${LLM_MODEL}",
"messages": [
{"role": "system", "content": "You are a senior ML reviewer (NeurIPS/ICML level)."},
{"role": "user", "content": "[Full review prompt]"}
],
"max_tokens": 4096
}'AUTO_REVIEW.md## Round N (timestamp)
### Assessment (Summary)
- Score: X/10
- Verdict: [ready/almost/not ready]
- Key criticisms: [bullet list]
### Reviewer Raw Response
<details>
<summary>Click to expand full reviewer response</summary>
[Paste the COMPLETE raw response here — verbatim, unedited.]
</details>
### Actions Taken
- [what was implemented/changed]
### Results
- [experiment outcomes, if any]
### Status
- [continuing to round N+1 / stopping]REVIEW_STATE.jsonREVIEW_STATE.jsoncat << 'EOF' > filemcp__llm-chat__chat:
system: "You are a senior ML reviewer (NeurIPS/ICML level)."
prompt: |
[Round N/MAX_ROUNDS of autonomous review loop]
## Previous Review Summary (Round N-1)
- Previous Score: X/10
- Previous Verdict: [ready/almost/not ready]
- Previous Key Weaknesses: [list]
## Changes Since Last Review
1. [Action 1]: [result]
2. [Action 2]: [result]
## Updated Results
[paste updated metrics/tables]
Please re-score and re-assess:
1. Score this work 1-10 for a top venue
2. List remaining critical weaknesses (ranked by severity)
3. For each weakness, specify the MINIMUM fix
4. State clearly: is this READY for submission? Yes/No/Almost
Be brutally honest. If the work is ready, say so clearly.