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tooluniverse-adverse-event-detection

Detect and analyze adverse drug event signals using FDA FAERS reports, drug labels, and disproportionality statistics (PRR, ROR, IC). Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, regulatory submissions, and detecting rare AE signals not visible in clinical trials.

65

Quality

78%

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SecuritybySnyk

Low

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tessl review fix ./plugin/skills/tooluniverse-adverse-event-detection/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, highly actionable overview for an expert-domain analysis pipeline, with clear sequencing, concrete tool calls, and sensible edge-case handling. Its critical defect is that all four referenced companion files are missing from the bundle, so every "See X.md" deferral dead-ends and the detailed scoring rubric, templates, and tool reference the skill depends on are unavailable.

Suggestions

Ship the four referenced files (PHASE_DETAILS.md, REPORT_TEMPLATE.md, TOOL_REFERENCE.md, QUICK_START.md) in the bundle, or remove the dangling references and inline only the essential content (signal classification table, Safety Signal Score rubric).

Include one small executable snippet in SKILL.md (e.g., a PRR/ROR with 95% CI computation via scipy) so the core disproportionality step is runnable even without PHASE_DETAILS.md.

De-duplicate the workflow: either the ASCII phase diagram or the Phase Summaries section can carry the per-phase detail, cutting ~40 lines without losing information.

DimensionReasoningScore

Conciseness

The body is dense and directive throughout — it names exact tool calls, thresholds ("PRR >= 2.0, N >= 3, lower CI > 1.0"), and Naranjo scoring values without explaining concepts Claude already knows. Minor duplication between the ASCII workflow diagram and the per-phase summaries (each phase name/purpose appears twice) keeps it below a 5.

4 / 5

Actionability

Concrete, executable guidance dominates: specific tool function names (`FAERS_calculate_disproportionality`, `OpenTargets_get_drug_chembId_by_generic_name`), explicit signal criteria, Naranjo point scoring, and a decomposed Safety Signal Score ("FAERS signal strength (0-35), serious AEs (0-30), FDA label warnings (0-25), literature evidence (0-10)"). It falls short of a 5 because key execution detail (code examples, output templates, full classification table) is deferred to `PHASE_DETAILS.md` and `REPORT_TEMPLATE.md`, which do not exist in the bundle.

4 / 5

Workflow Clarity

Ten phases are clearly sequenced with an overview diagram, per-phase summaries, a flagged "CRITICAL PHASE", and an Edge Cases section covering failure modes ("`{error: {code: "NOT_FOUND"}}` is normal when a section does not exist", "No FAERS reports: Skip Phases 1-2") and a completeness checklist. Not a 5 because the validation/checklist mechanics and full scoring rubric are deferred to missing files, leaving the error-recovery loop implicit in SKILL.md itself.

4 / 5

Progressive Disclosure

The body correctly signals one-level-deep references ("See `PHASE_DETAILS.md` for full signal classification table"), but none of the four referenced files (`PHASE_DETAILS.md`, `REPORT_TEMPLATE.md`, `TOOL_REFERENCE.md`, `QUICK_START.md`) exist in the bundle — there are no references/, scripts/, or assets/ directories. Scored against the actual bundle structure per the judging guidelines, the deferred content is inaccessible, so navigation breaks exactly where the skill points the reader.

2 / 5

Total

14

/

20

Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, well-formed description: concrete capabilities with named methods and outputs, an explicit 'Use for' trigger clause, and good natural keyword coverage in the domain vocabulary. The only refinements worth making are adding common user synonyms and signaling its boundary against the sibling pharmacovigilance skill.

DimensionReasoningScore

Specificity

Multiple concrete capabilities are named with their methods and outputs: "Detect and analyze adverse drug event signals using FDA FAERS reports, drug labels, and disproportionality statistics (PRR, ROR, IC)" plus "Generates quantitative safety signal scores (0-100) with evidence grading". Coverage of the domain is comprehensive and entirely free of vague filler.

5 / 5

Completeness

Both halves are explicit: the "what" states the detection methods, data sources, and output (quantitative 0-100 safety signal scores with evidence grading), and the "Use for" clause lists concrete triggers (post-market surveillance, pharmacovigilance, drug safety assessment, regulatory submissions, detecting rare AE signals not visible in clinical trials).

5 / 5

Trigger Term Quality

Strong natural terms a pharmacovigilance user would say: "post-market surveillance", "pharmacovigilance", "drug safety assessment", "regulatory submissions", "adverse drug event", "FAERS". Below a 5 because common lay/clinical synonyms like "side effects", "safety profile", or "drug safety comparison" are missing as trigger phrasings.

4 / 5

Distinctiveness Conflict Risk

The niche is clear and the statistical framing (FAERS, PRR/ROR/IC, signal scores) is distinct from generic analysis skills. Held at 4 because the body acknowledges a sibling skill "tooluniverse-pharmacovigilance" covering adjacent ground, and the description does not itself draw that boundary — a user asking broadly for "pharmacovigilance" could reasonably match either.

4 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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