Content
81%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-engineered clinical workflow: fully executable commands, a numeric scoring rubric, explicit validation gates, and a completion checklist. Its weaknesses are token efficiency — basic pharmacology explanations and the valproate+lamotrigine case repeated three times — and inlining of stable reference tables that belong in a separate reference file behind the otherwise excellent script integration.
Suggestions
Move the 13-row interaction table, the UGT deep-dive, and the transporter substrate/inhibitor lists into a references/ file (e.g. references/interaction_catalog.md), keeping only the most critical pairs and a pointer in SKILL.md — this serves both the conciseness and progressive-disclosure gaps.
Cut textbook definitions Claude already knows (what UGT conjugation does, why induction is slow, the inhibitor-up/inducer-down rule) and state each rule once; the valproate+lamotrigine example currently appears in the table, the paradigm section, and the ADR example — keep one full treatment and reference it from the others.
Deduplicate the reasoning guidance that appears in both 'Clinical Reasoning Framework' and 'Tool Workflow Phase 1-2' (e.g., apply CYP reasoning before database queries is instructed twice).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~340-line body is mostly purposeful, but it explains foundational pharmacology Claude already knows ("UGT enzymes... conjugate drugs with glucuronic acid for renal elimination", "Induction takes days to weeks to develop (requires new enzyme protein synthesis)", the inhibitor-up/inducer-down rule stated in at least three places) and repeats the valproate+lamotrigine case across the table, a dedicated paradigm section, and the ADR example. This matches the score-3 anchor (mostly efficient, some unnecessary explanation, could be tightened); it is not a 2 because the padding is domain heuristics rather than generic filler, and not a 4 because the repetition and textbook definitions are genuinely trimmable. | 3 / 5 |
Actionability | Fully executable throughout: copy-paste-ready CLI examples for every `pharmacology_ref.py --type` mode (verified against the actual bundled script), a numeric risk-scoring formula ("Major=60, Moderate=35... FDA label +20"), a named report file convention (`DDI_risk_report_[DRUG1]_[DRUG2].md`), specific tool names per phase, and a 10-section output template. Matches the score-5 anchor — concrete commands with examples covering the common cases. | 5 / 5 |
Workflow Clarity | Clear six-phase sequence (identification → PK → PD → evidence → scoring → alternatives) with explicit checkpoints: the mandatory report-first pattern with `[Analyzing...]` placeholders, "Document failed tool calls explicitly", a "Validate: Does the predicted mechanism match the clinical magnitude?" step in ADR attribution, and a final 16-item Success Criteria checklist gating report completion ("All sections completed (no [Analyzing...] placeholders)"). This is the score-5 shape: sequenced steps with explicit validation and a completion checklist; a 4 would lack the final gate or error-recovery guidance. | 5 / 5 |
Progressive Disclosure | The bundle script is well integrated: clearly signaled at the top ("LOCAL PHARMACOLOGY REFERENCE (USE FIRST)"), one level deep, real (all documented --type flags exist in the file), with key findings summarized inline in the severity table. Not a 5 because ~150 lines of stable reference material (the 13-row interaction table, the UGT deep-dive, transporter substrate/inhibitor lists) are inlined in SKILL.md rather than split into a references/ file, which would keep the overview lean. This sits squarely in the score-4 anchor (good structure, most content appropriately placed, minor organization gaps); not a 3 because the structure is genuinely well-sectioned and the one external reference is clearly navigable. | 4 / 5 |
Total | 17 / 20 Passed |