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.
How to install debug?
fcakyon/phd-skills/debug
$npx -y skills add fcakyon/phd-skills --skill debugInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/fcakyon/phd-skills" --skill "fcakyon/phd-skills/debug"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/fcakyon/phd-skills" that are relevant to the current task. Run `npx skills add "https://github.com/fcakyon/phd-skills"` and select the relevant skills, then follow their instructions.
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