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safe-debug

Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training

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安装到 Tokeny(自动)

下载 ZIP
安装"safe-debug"技能
技能信息:
- 名称: safe-debug
- 标识: safe-debug
- 描述: Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training
- 版本: 1f652d9
下载地址:
https://www.tokeny.space/api/skills/safe-debug/download
继续

复制上方内容到 Tokeny 客户端并在会话中发送即可自动安装;也可直接 下载 ZIP并拖动到技能窗口安装。

SKILL.md

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.md
  • debug_outputs/PATCH_PLAN.md
  • debug_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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