Mostly efficient domain-specific guidance, but the ~800-line body is padded with invented mock-data output tables (e.g., '45,234 reports', fabricated PMIDs) that could be tightened; not 3 because verbosity is present, not 1 because it avoids re-explaining concepts Claude already knows.

Provides copy-paste-ready Python functions with concrete tool calls and parameters (e.g., FAERS_count_reactions_by_drug_event with drug_name), plus a parameter-correction table and fallback chains — fully executable guidance.

Clear phased sequence (Phase 0-7) with explicit validation: Phase 0 tool-parameter verification, a per-phase completeness checklist, and fallback chains give explicit checkpoints and recovery paths.

Good internal section structure but the skill is a single 800-line monolith with content that should be split inline, and its only external reference ([TOOLS_REFERENCE.md]) is a dangling link to a file that does not exist; not 1 because section headers provide real organization, not 3 because no valid one-level-deep bundle reference exists.

Lists multiple concrete actions — 'Analyze drug safety signals', 'Calculates disproportionality measures (PRR, ROR)', 'identifies serious adverse events', 'assesses pharmacogenomic risk variants' — matching the multiple-specific-actions anchor.

Explicitly answers both what (analyze signals, calculate PRR/ROR, identify serious AEs, assess PGx variants) and when (explicit 'Use when...' clause), so it is not capped at 2.

'Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment' covers natural terms a user would actually say; not 2 because common variations are well represented rather than partially missing.

The pharmacovigilance/drug-safety niche with FDA adverse-event and PGx triggers is clearly distinct and unlikely to fire for unrelated skills.