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The skill was thorough but failed to instill debugging taste: an agent would pattern-match a symptom-table row to a fix and ship a guess, because the behaviour-changing material sat 550 lines down. Promote three gates to the top: - "Before you debug: calibrate" -- you're likely OOD in research code; the failure mode is overconfidence/impatience; the tables are a menu to widen the search, never lookup-and-apply. - "The debugging loop (judgment, not a checklist)" -- collect clues, hold a few competing hypotheses scaled to the problem, sanity-check with the likely/subtle/null triplet (shared vocab with research-journal), run the cheapest discriminating observation, then act. - "When stuck, read a working implementation" -- promoted from a buried Part 7.3 one-liner; extract the algorithm-done-right, the engineering tricks the paper omits, and proven hyperparams; rank candidates by trust signal. Collapse duplicated advice to pointers; de-bold Part 6.4 (8 bolded openers -> a plain list). Net +10 lines, bold markers 112 -> 100. Verified by a blind comprehension-by-inference quiz (5 cold-reader models, OLD vs NEW): NEW 9.6/10 vs OLD 6.8/10, with the gap localized to the two added sections (read-working-impl 5/5 vs 0/5; tables-as-menu 2.0 vs 1.6) while untouched sections tied -- ruling out a "reads nicer" halo. Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
ML Debugging Folklore
Practitioner knowledge for debugging ML systems, curated and synthesized by wassname. Opinionated by source selection -- I picked sources I trust (Schulman, Goodfellow, CS231n, ...) and had an LLM extract the most relevant information for debugging ML systems.
Use as a Claude skill
/skills add https://github.com/wassname/ml_debug
Or paste SKILL.md into your system prompt / context when debugging.
What's here
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SKILL.md -- the main artifact. Load into an LLM agent's context as a debugging skill. Parts 1-5 are reference knowledge; Part 6 is a runnable triage protocol (grep patterns, diagnostic snippets, decision tree); Part 7 is debugging mental models and practitioner priors.
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docs/evidence/ -- frozen local copies of source material (blog posts, talks, papers, reddit threads). Claims in SKILL.md link back to exact quotes here.
Description
skill for debugging and dev of machine learning, collected over the years in an attempt to uplift agents (and myself)
3.7 MiB
Languages
Python
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Just
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