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 ../ai-research-reproduction/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, ../ai-research-reproduction/references/research-rigor-principles.md, and the shared ../ai-research-reproduction/references/research-pitfall-checklist.md.