wassname 779beee03e refactor(ml_debug): tidy ordering/emphasis on the new top sections
Three targeted polishes to the rewritten skill:
- Reframe Part 1's "The hierarchy (work in order...)" -> "What 'collect clues'
  looks like": it's the catalog the loop's clue-collection step draws on, not a
  second master-procedure competing with "the debugging loop" 40 lines above.
- Reorder: lead straight into calibrate -> loop -> read-impl; relocate the
  2017-2021 caveat + LLM-pretraining pointers into a "Scope and modern pointers"
  block after the action sections, so the behaviour-changing content is the
  first screen instead of provenance.
- Emphasis: give the "priors are a starting weight, not a verdict" line a
  concrete clause (traceback / loss-metric misalignment / right init-loss
  override the data prior) -- the weakest comprehension dim in the quiz.

Before-vs-after panel A/B (6 cold readers): tie on ordering/clarity/
conciseness/focus, each leaning slightly positive, no regression.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
2026-06-01 10:15:41 +08:00
2026-04-09 05:09:25 +08:00
2026-04-09 05:09:25 +08:00

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

  • 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.

  • docs/evidence/ -- frozen local copies of source material (blog posts, talks, papers, reddit threads). Claims in SKILL.md link back to exact quotes here.

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