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tooluniverse-clinical-trial-matching

AI-driven patient-to-trial matching for precision oncology and rare-disease care. Transforms a patient's molecular profile (mutations, biomarkers, expression) and clinical state into ranked clinical-trial recommendations with evidence tiers. Searches ClinicalTrials.gov, the EU CTIS register (European/EEA trials), AND the ISRCTN registry (UK/international) plus cross-references CIViC, OpenTargets, ChEMBL, and FDA labels. Use for matching patients to trials by genotype, biomarker-driven trial selection, trial-eligibility scoring, and finding trials across the US, Europe, and the UK.

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

75%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.

A well-structured, information-dense skill body with a clear ten-phase workflow, concrete tool parameters, scoring rubrics, and error-handling guidance. Main gaps are the broken KEY PRINCIPLES list, duplication between the inline tool/scoring tables and the referenced files, and the absence of worked examples in the body itself.

Suggestions

Fix the broken "KEY PRINCIPLES" numbered list: items 4-10 currently sit after the "Molecular Matching Priority" section, splitting one list across two sections — either move items 4-10 up with items 1-3 or renumber them as a separate list.

Move the inline Critical Tool Parameters tables, Scoring Summary, and Known CIViC Gene IDs into TOOLS_REFERENCE.md and SCORING_CRITERIA.md, keeping only a brief pointer in SKILL.md, to remove duplication and shrink the context cost.

Integrate validation checkpoints into the phase workflow itself (e.g. after Phase 2 verify the merged NCT/CT/ISRCTN ID list is non-empty and deduplicated, and after Phase 3 confirm eligibility text was retrieved for each trial) rather than only in the separate Error Handling section.

DimensionReasoningScore

Conciseness

The body is dense and efficient — tables of tool parameters, point-scoring rubrics, and parallelization groups with no explanations of concepts Claude already knows. However, the Critical Tool Parameters tables, Scoring Summary, and hardcoded "Known CIViC Gene IDs" list duplicate material the Reference Files table assigns to TOOLS_REFERENCE.md and SCORING_CRITERIA.md, so not every token earns its place. Fits the 4 anchor (efficient, minor instances that could be trimmed) rather than 5.

4 / 5

Actionability

Guidance is concrete and executable in spirit: exact tool names with required parameters ("action must be exactly 'search_studies'", "ALL 4 parameters... REQUIRED"), batch size of 10, a 0-100 scoring breakdown, and parallelization groups. It falls short of 5 because the body contains no worked search-query or code examples — those are deferred to EXAMPLES.md and TRIAL_SEARCH_PATTERNS.md, leaving minor gaps in copy-paste-ready guidance.

4 / 5

Workflow Clarity

The ten phases are clearly sequenced with inputs/outputs per phase, parallelization groups, and an Error Handling section (try/except per call, empty-result checks, fallback tools, documented failures) that serves as validation for the batch operations, so it does not hit the batch-operation cap of 3. It is not 5 because checkpoints are described in a separate section rather than integrated as explicit per-phase validation steps, and the "KEY PRINCIPLES" list is structurally broken — items 4-10 are orphaned under the "Molecular Matching Priority" heading, interrupting the sequence.

4 / 5

Progressive Disclosure

The body is an overview with a Reference Files table signaling seven one-level-deep references with their contents, which is good structure. It is not 5 because substantial reference material (the full tool parameter tables, CIViC gene ID lookup, detailed scoring tables) is inlined rather than split into those files, creating duplication, and none of the seven referenced files exist in the provided bundle to verify the links resolve.

4 / 5

Total

16

/

20

Passed

Description

92%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 description: concrete, comprehensive, third-person, and explicitly stating both what it does and when to use it with named data sources. The only weakness is trigger-term coverage that leans technical (registry and database names) while missing a few natural user phrasings for trial searching.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions with comprehensive coverage: "Transforms a patient's molecular profile (mutations, biomarkers, expression) and clinical state into ranked clinical-trial recommendations with evidence tiers", "Searches ClinicalTrials.gov, the EU CTIS register... AND the ISRCTN registry", and "cross-references CIViC, OpenTargets, ChEMBL, and FDA labels" — all in consistent third-person voice. It clearly matches the 5 anchor (multiple specific concrete actions); there is no vagueness that would drop it to 4.

5 / 5

Completeness

It explicitly answers both questions: the "what" is stated concretely ("Transforms a patient's molecular profile... into ranked clinical-trial recommendations with evidence tiers") and the "when" is an explicit trigger clause ("Use for matching patients to trials by genotype, biomarker-driven trial selection, trial-eligibility scoring, and finding trials across the US, Europe, and the UK"). This matches the 5 anchor exactly; 4 would require a weaker or less explicit 'when' clause.

5 / 5

Trigger Term Quality

Natural phrases like "matching patients to trials", "biomarker-driven trial selection", "trial-eligibility scoring", and "finding trials across the US, Europe, and the UK" give good keyword coverage, but common user phrasings (e.g. "find clinical trials for my cancer", "trial search", "enrollment options") are missing and the term list leans technical (register and database names). This fits the 4 anchor (good coverage, a few natural terms missing) rather than 5 (comprehensive synonyms).

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (AI-driven patient-to-trial matching for precision oncology and rare-disease care) with triggers specific to trial matching by genotype and biomarker, so overlap with adjacent bioinformatics skills (variant interpretation, drug safety, target validation) is minimal. Matches the 5 anchor (clear niche with distinct triggers); 4 would imply minor overlap risk that is not evident here.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 9 missing

Warning

Total

15

/

16

Passed

Repository

mims-harvard/ToolUniverse

Path

plugin/skills/tooluniverse-clinical-trial-matching/SKILL.md

Reviewed

Table of Contents

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