ML Debugging

Systematically diagnose ML failures using framework-specific knowledge, not guesswork.

Grounding

Detect mode: On your first grounding call, check if Leeroopedia KB tools are available. If they return results, use KB mode. If unavailable or auth fails, use Web mode.

HARD RULE: You MUST ground before writing analysis. If KB fails, you MUST WebFetch at least 2 URLs before writing ANY diagnosis. Writing from memory without fetching is the #1 failure mode of this skill — it produces zero-citation responses that score 0/3 on grounding. "I know X well" is NOT a substitute for fetching documentation.

KB mode: Call diagnose_failure → query_hyperparameter_priors → search_knowledge. Cite as [PageID].

KB mode grounding supplement (MANDATORY): After KB calls, you MUST WebFetch at least 2 public URLs (official docs, PyPI, GitHub issues/source) and cite them as [source](URL) alongside [PageID] citations. KB-only responses score 2/3 max on grounding because reviewers cannot verify proprietary page IDs. Pattern: KB call for diagnosis → WebFetch PyPI for version → WebFetch GitHub/docs for config verification → cite BOTH KB and public URLs in every section. Self-test: if your response has zero [source](URL) citations, you will lose a grounding point regardless of KB citation count.

Web mode: WebFetch GitHub issues for the error message → WebFetch framework troubleshooting docs → WebFetch config references. Cite as [source](URL). Start response with: > Grounding: Web mode — citations from official docs and GitHub issues.