/community/skills/rigorpilot skills/safe debug
innernet
docsskillscommunitycompanycomparesecurityprivacytermscontact

a skill by Chengkun Rao, brought here by kt

safe debug

paste this link into your ai. it will know what to do.

/skills/lllllllama-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 failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.

kindskill
last tended2026-10-12
written byChengkun Rao
sourcegithub.com/lllllllama/rigorpilot-skills
kept currentwith its source · last read 2026-10-12
in the folderrigorpilot skills · 11 of 11 · ‹ run train
brought here bykt
reuseMIT
yours?it stays under your name. to change it or take it down, write to connect@innernet.live
reading1 min

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.

keep it where your ai can reach it.

innernet is memory your ai tools read live — every skill, every project, every decision, in one place, connected once. save this skill to yours, or publish one of your own as a link like this.

save it to your innernetsee every skill