Mostly efficient but the inline biomarker-to-drug mapping tables (NSCLC, Breast, Colorectal, Melanoma, tumor-agnostic) and resistance-mechanism lists are large reference data that could live in TREATMENT_ALGORITHMS.md rather than the body; the Phase 0 correction table also repeats parameter guidance already given later.

Provides concrete, executable guidance: exact tool names with correct parameter names and examples ('condition', NOT 'disease'; 'ensemblId' camelCase; molecular_profile="EGFR C797S"), plus a worked cross-skill script invocation.

Clear phased sequence (Phase 0–6) with explicit validation checkpoints — Phase 0 tool-verification table, MANDATORY FAERS/FDA calls with 'do NOT skip', and a 'LOOK UP DON'T GUESS' guard against assuming from memory.

Body signals one-level-deep references (TOOLS_REFERENCE.md, API_USAGE_PATTERNS.md, etc.) and points to a scripts file, but those reference files are not present in the bundle, so the disclosure structure is claimed but not actually realized on disk.

Lists multiple concrete actions: 'FDA-approved + investigational therapies, resistance mechanisms, matching clinical trials, prognosis' and names specific databases (CIViC, ClinVar, OpenTargets, ClinicalTrials.gov).

Explicitly answers both what ('Cancer treatment recommendations from molecular profile...') and when via the 'Use for tumor-board treatment recommendations, evidence-tiered actionability assessment, and FDA-precedent-driven therapy selection' clause.

Covers natural terms users would say — 'cancer', 'tumor-board treatment recommendations', 'clinical trials', 'therapy selection', 'biomarkers' — plus domain-specific triggers like 'evidence-tiered actionability assessment'.

Clear niche — precision oncology molecular-profile-driven treatment advice — with distinct triggers (tumor-board, FDA-precedent-driven therapy selection) unlikely to conflict with other skills.