safe-debug
此技能专为深度学习研究工作中的调试与审计设计。当用户遇到追溯错误、终端报错、CUDA OOM、检查点加载失败、形状不匹配或训练故障等问题时,该 Skill 能提供保守的诊断和最小化的修复建议,且明确区分调试修复与研究贡献,从而帮助用户快速定位并解决问题,保障研究流程的严谨性与效率。
npx skills add https://github.com/lllllllama/rigorpilot-skills --skill safe-debugBefore / After 效果对比
1 组在没有此技能之前,开发者在深度学习研究中遇到复杂错误时,需要手动耗费大量时间分析堆栈跟踪、日志和代码,以定位根本原因。这不仅效率低下,还可能在调试过程中无意引入新的问题或混淆研究成果,导致项目延期。
该 Skill 能够快速诊断深度学习错误,提供精确且最小化的修复建议,并明确区分调试与研究贡献。此技能显著缩短了故障排除时间,降低了引入新错误的风险,并确保了研究代码的纯净性,极大地提升了开发者的工作效率和研究质量。
safe-debug
Use this as the Rigor Debug / Rigor Audit skill. The installed slug remains
safe-debug for compatibility.
Use the shared operating principles in
../../references/agent-operating-principles.md; this skill should guide
conservative diagnosis without blocking the model from finding the local root
cause.
When to apply
- The user provides a traceback, terminal error, or concrete training or inference failure symptom.
- The user wants diagnosis, root-cause narrowing, and minimal patch suggestions before code is changed.
- The user wants a safe debug flow with explicit human approval before mutation.
When not to apply
- When the user wants a broad repository walkthrough without an active failure.
- When the task is speculative experimentation or code adaptation.
- When the user is asking for a large refactor or readability rewrite.
Clear boundaries
- Diagnose first.
- Do not modify repository code by default.
- If a patch is needed, propose the smallest fix and require explicit approval first.
- Escalate savepoint or branch creation before medium-risk or high-risk changes.
- A debug fix is not automatically a research contribution; if it changes experiment meaning or comparability, say so explicitly.
Output expectations
debug_outputs/DIAGNOSIS.mddebug_outputs/PATCH_PLAN.mddebug_outputs/status.json
Notes
Use references/debug-policy.md, ../../references/research-rigor-principles.md, and the shared references/research-pitfall-checklist.md.
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