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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

84%

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is tooluniverse-clinical-trial-matching in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

71%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.

An information-dense, highly actionable instruction skill with a clearly sequenced 10-phase workflow, concrete tool parameter tables, and real error-handling guidance. Its main defects are structural: the KEY PRINCIPLES list is split/orphaned mid-document, and all seven referenced bundle files are missing, leaving key details (scoring logic, matching algorithms, report template) unreachable.

Suggestions

Ship the referenced bundle files (MATCHING_ALGORITHMS.md, SCORING_CRITERIA.md, TOOLS_REFERENCE.md, REPORT_TEMPLATE.md, TRIAL_SEARCH_PATTERNS.md, EXAMPLES.md, QUICK_START.md) or remove/inline the dead links — progressive_disclosure currently points at files that do not exist, so delegated details like scoring logic and the report template are unreachable.

Fix the broken 'KEY PRINCIPLES' list: items 4–10 (Evidence-graded through English-first queries) are stranded under the '## Molecular Matching Priority' heading; rejoin them with items 1–3 under a single list or renumber them as their own section.

Add one or two fully-specified example tool invocations (e.g., a `search_clinical_trials` and `CTIS_search_trials` call with concrete argument values) so the top-scoring use cases are copy-paste ready without consulting the missing reference files.

DimensionReasoningScore

Conciseness

The body is dominated by dense, non-obvious reference material (MCP tool parameter tables, required-parameter warnings, CIViC gene IDs, point-valued scoring tables) that Claude cannot know. Minor trimmable redundancy: the opening paragraph restates the frontmatter description, and 'LOOK UP, DON'T GUESS' spends lines telling Claude to prefer verified data. Not 5: these minor padded spots exist; not 3: no explanations of concepts Claude already knows.

4 / 5

Actionability

Concrete, near-executable guidance throughout: exact tool names with required parameters ("`drugbank_get_targets_by_drug_name_or_drugbank_id` | `query`, `case_sensitive`, `exact_match`, `limit` (ALL REQ)"), batch sizes ("process in batches of 10"), explicit scoring arithmetic, and parallelization groups. Not 5: no example tool invocations with actual argument values, and critical logic (biomarker parsing, detailed scoring, report template) is delegated to reference files; not 3: far more executable than pseudocode-level guidance.

4 / 5

Workflow Clarity

The 10-phase workflow is clearly sequenced with a parallelization strategy and error handling that includes try/except wrapping, empty-result checks, fallback tools, and failure documentation in a completeness checklist — so batch operations do have validation/verification steps. Not 5: the 'KEY PRINCIPLES' numbered list is structurally broken — items 4–10 are orphaned under the 'Molecular Matching Priority' heading after its paragraph, muddling the principle list — and phase details are thin (one line each), leaving some checkpoints implicit.

4 / 5

Progressive Disclosure

The body is well-sectioned and the trailing 'Reference Files' table clearly signals one-level-deep references, but every referenced file (TOOLS_REFERENCE.md, MATCHING_ALGORITHMS.md, SCORING_CRITERIA.md, REPORT_TEMPLATE.md, TRIAL_SEARCH_PATTERNS.md, EXAMPLES.md, QUICK_START.md) is absent from the bundle — the references/ directory does not exist, so all seven links are dead and navigation breaks. Not 4: scoring against the actual bundle structure, clearly-signaled references that do not resolve cannot count as good structure; not 2: the in-body organization and reference signaling are present and reasonable.

3 / 5

Total

15

/

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, third-person, comprehensive in naming both capabilities and data sources, with an explicit 'Use for' trigger clause. The only weakness is trigger phrasing that leans clinical/technical, missing a few natural lay terms a patient or general user might say.

DimensionReasoningScore

Specificity

"Transforms a patient's molecular profile (mutations, biomarkers, expression) and clinical state into ranked clinical-trial recommendations with evidence tiers" and "Searches ClinicalTrials.gov, the EU CTIS register... AND the ISRCTN registry plus cross-references CIViC, OpenTargets, ChEMBL, and FDA labels" list multiple concrete actions with named data sources, comprehensively covering the skill's capability. Not 4: there are no coverage gaps — inputs, transformation, output (rankged, evidence-tiered recommendations), and sources are all explicit; uses third person throughout.

5 / 5

Completeness

Explicitly answers both what ("Transforms a patient's molecular profile... into ranked clinical-trial recommendations with evidence tiers") and when ("Use for matching patients to trials by genotype, biomarker-driven trial selection, trial-eligibility scoring...") with concrete trigger phrases. Not 4: the when-clause is explicit and enumerates specific use scenarios rather than a vague condition.

5 / 5

Trigger Term Quality

"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" provides good natural keywords ("clinical trial", "matching", "eligibility", "biomarker"), but the phrasing is technical and misses common lay variations like "cancer trials", "experimental treatments", or "enroll in a trial". Not 5: synonym coverage is not comprehensive; not 3: well above the 'some relevant keywords' anchor.

4 / 5

Distinctiveness Conflict Risk

"AI-driven patient-to-trial matching for precision oncology and rare-disease care" with named registers (ClinicalTrials.gov, CTIS, ISRCTN) carves a clear niche distinct from variant interpretation, drug safety, or general disease-research skills. Not 4: the trial-matching focus plus unique source set gives minimal overlap risk.

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

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

Reviewed

Table of Contents

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