Individual skill
debug
Evidence-before-action diagnosis of failing ML experiments. Probes the system before guessing causes, process list, dmesg, GPU stats, log scrollback, checkpoint state, then states a hypothesis as a hypothesis and runs a smoke before claiming a root cause. Use when the user asks why a run is failing, diverging, OOMing, hanging, slow, producing weird metrics, has crashed, or asks to debug, diagnose, troubleshoot, or investigate a training issue.
plugin/skills/debug/SKILL.md
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- Last checked
- Nov 5, 2026
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- Nov 1, 2026
- License
- MIT
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# Debug: evidence-before-action investigation
The most expensive class of mistake in ML debugging is asserting a cause based on plausibility, then attempting a "fix" that masks the real problem. This skill enforces the discipline of probe → hypothesis → smoke → controls → claim, in that order.
The agentic Stop hook routes here from `reason` when an assistant claims a cause without backing tool output.
## When to run
The user just said any of:
- "why is X failing / diverging / NaN / OOM / hung / slow / crashed"
- "the loss is going up", "metrics look weird", "GPU util is 0"
- "debug this", "diagnose", "troubleshoot", "investigate this run"
- pasted a log excerpt asking what's wrong