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Record coding attempts, compare verdicts, and improve LLM judging accuracy.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "handson-coding" yet — see the docs or source repo.
Record this coding practice submission, compare the platform's official result with the LLM verdict, and summarize the reasons for any misjudgment.
A practice log containing both verdicts, their differences, and a summary of misjudgment causes.
Based on the last 20 coding practice cases where the LLM and platform results disagreed, derive reusable correction rules for judging.
A set of actionable correction rules that reduce future judging errors and explain when to apply them.
Analyze how the LLM judging accuracy changed over the past month and compare performance before and after applying correction rules.
A trend analysis showing accuracy changes, key improvements, and recommendations for further optimization.
Delegate long-running task decisions to an OpenAI reviewer for structured next steps.
Let your AI coding agent self-host open-source apps with deployment and security setup.
Coordinate Codex and local Claude Code for engineering, review, and automation workflows.
Scan, store, and semantically search codebase API endpoints for faster coding.
Automatically distill, update, and prune reusable skills from real coding sessions.
Lets MCP coding agents read and control browser pages with human-like actions.