auto-review-loop-llm
SolidAutonomous 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".
Install
Quality Score: 93/100
Skill Content
Details
- Author
- wanshuiyin
- Repository
- wanshuiyin/Auto-claude-code-research-in-sleep
- Created
- 2 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
auto-review-loop-minimax
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
auto-review-loop
Autonomous multi-round research review loop. Repeatedly reviews using a secondary Codex agent, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
review-llm-artifacts
Detects common LLM coding agent artifacts by spawning four parallel subagents over the project or changed files. Scans files changed since main by default; use --all for full-project scan. Triggers on LLM cruft cleanup, agent-generated code review, dead code sweeps, test-quality passes, or when the user asks to scan the whole repo.
review-loop
Cross-LLM iterative code review loop. Spawns a peer reviewer (Codex, Claude, or Gemini CLI) to review code changes, then iterates until both agents agree on the final code state. Code gets modified during the loop — the final output is improved code + consensus report. Use when: "review loop", "peer review", "cross review", "review with codex", "review with claude", "review with gemini", "让 codex review", "让 claude review", "交叉 review", "peer review 这段代码", "code review loop", "iterative review"
llm-evaluation
Model output quality assessment, hallucination detection, benchmark suites. [EXPLICIT] Trigger: "llm evaluation"