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Agent skill

Tooluniverse Clinical Trial Matching

by aipoch in aipoch/medical-research-skills

AI-driven patient-to-trial matching for precision medicine and oncology.

MITAuto-check passedResearch & Science

Install Tooluniverse Clinical Trial Matching

skills CLI
$ npx skills add aipoch/medical-research-skills --skill tooluniverse-clinical-trial-matching -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills tooluniverse-clinical-trial-matching --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Evidence Insight/tooluniverse-clinical-trial-matching' .claude/skills/tooluniverse-clinical-trial-matching && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tooluniverse-clinical-trial-matching
GitHub stars
1.9k
Token cost
~2.6k tokens
SKILL.md length
1,038 words
Files
9 (incl. references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

AI-driven patient-to-trial matching for precision medicine and oncology.

  • Works in 10 steps: Report-first approach - Create report… → Patient-centric - Every recommendation… → Molecular-first matching - Prioritize… → …
  • Tasks that involve Clinical and healthcare research
  • SKILL.md covers When to Use, Input Parsing, Workflow Overview and Trial Match Score (0-100), plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tooluniverse Clinical Trial Matching is an agent skill from aipoch/medical-research-skills. AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility...

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `EXAMPLES.md`, `POLISH_CHANGELOG.md` and `QUICK_START.md`).

It sits in Research & Science, covering Clinical and healthcare research. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Tasks that involve Clinical and healthcare research

Example prompts

  • “/tooluniverse-clinical-trial-matching”

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Report-first approach - Create report file FIRST, then populate progressively
  2. Patient-centric - Every recommendation considers the individual patient's profile
  3. Molecular-first matching - Prioritize trials targeting patient's specific biomarkers
  4. Evidence-graded - Every recommendation has an evidence tier (T1-T4)
  5. Quantitative scoring - Trial Match Score (0-100) for every trial
  6. Eligibility-aware - Parse and evaluate inclusion/exclusion criteria
  7. Actionable output - Clear next steps, contact info, enrollment status
  8. Source-referenced - Every statement cites the tool/database source
  9. Completeness checklist - Mandatory section showing analysis coverage
  10. English-first queries - Always use English terms in tool calls. Respond in user's language

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tooluniverse Clinical Trial Matching loads about 2.6k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 1,038 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~19k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,038 words, ~2,568 tokens.

Download SKILL.mdSave it as .claude/skills/tooluniverse-clinical-trial-matching/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
tooluniverse-clinical-trial-matching
description
AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility...
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Clinical Trial Matching for Precision Medicine

Transform patient molecular profiles and clinical characteristics into prioritized clinical trial recommendations. Searches ClinicalTrials.gov and cross-references with molecular databases (CIViC, OpenTargets, ChEMBL, FDA) to produce evidence-graded, scored trial matches.

KEY PRINCIPLES:

  1. Report-first approach - Create report file FIRST, then populate progressively
  2. Patient-centric - Every recommendation considers the individual patient's profile
  3. Molecular-first matching - Prioritize trials targeting patient's specific biomarkers
  4. Evidence-graded - Every recommendation has an evidence tier (T1-T4)
  5. Quantitative scoring - Trial Match Score (0-100) for every trial
  6. Eligibility-aware - Parse and evaluate inclusion/exclusion criteria
  7. Actionable output - Clear next steps, contact info, enrollment status
  8. Source-referenced - Every statement cites the tool/database source
  9. Completeness checklist - Mandatory section showing analysis coverage
  10. English-first queries - Always use English terms in tool calls. Respond in user's language

When to Use

Apply when user asks:

  • "What clinical trials are available for my NSCLC with EGFR L858R?"
  • "Patient has BRAF V600E melanoma, failed ipilimumab - what trials?"
  • "Find basket trials for NTRK fusion"
  • "Breast cancer with HER2 amplification, post-CDK4/6 inhibitor trials"
  • "KRAS G12C colorectal cancer clinical trials"
  • "Immunotherapy trials for TMB-high solid tumors"
  • "Clinical trials near Boston for lung cancer"
  • "What are my options after failing osimertinib for EGFR+ NSCLC?"

NOT for (use other skills instead):

  • Single variant interpretation without trial focus -> Use tooluniverse-cancer-variant-interpretation
  • Drug safety profiling -> Use tooluniverse-adverse-event-detection
  • Target validation -> Use tooluniverse-drug-target-validation
  • General disease research -> Use tooluniverse-disease-research

Input Parsing

Required Input
  • Disease/cancer type: Free-text disease name (e.g., "non-small cell lung cancer", "melanoma")
  • Molecular alterations: One or more biomarkers (e.g., "EGFR L858R", "KRAS G12C", "PD-L1 50%", "TMB-high")
  • Stage/grade: Disease stage (e.g., "Stage IV", "metastatic", "locally advanced")
  • Prior treatments: Previous therapies and outcomes (e.g., "failed platinum chemotherapy", "progressed on osimertinib")
Optional
  • Performance status: ECOG or Karnofsky score (e.g., "ECOG 0-1")
  • Geographic location: City/state for proximity filtering (e.g., "Boston, MA")
  • Trial phase preference: I, II, III, IV, or "any"
  • Intervention type: drug, biological, device, etc.
  • Recruiting status preference: recruiting, not yet recruiting, active
Biomarker Parsing Quick Reference
Input FormatParsed AsExample
Gene + amino acid changeSpecific mutationEGFR L858R
Gene + exon notationExon-level alterationEGFR exon 19 deletion
Gene + fusion partnerFusionEML4-ALK fusion
Gene + amplificationCopy number gainHER2 amplification
Gene + expression levelExpression biomarkerPD-L1 50%
Gene + statusStatus biomarkerMSI-high, TMB-high
Gene + resistanceResistance mutationEGFR T790M
Gene Symbol Normalization
Common AliasOfficial SymbolNotes
HER2ERBB2Search both in trials
PD-L1CD274Often searched as "PD-L1" in trials
ALKALKEML4-ALK is a fusion
VEGFVEGFAOften searched as "VEGF"
PD-1PDCD1Search as "PD-1" in trials
BRCABRCA1/BRCA2Specify which BRCA gene

Detailed parsing rules and regex patterns: see references/parsing_and_validation.md

Workflow Overview

PhaseNameSummary
0Tool Parameter ReferenceVerify all tool parameters before calling. See references/phases_detail.md
1Patient Profile StandardizationResolve disease→EFO ID, genes→Ensembl/Entrez IDs, classify biomarker actionability
2Broad Trial DiscoveryDisease/biomarker/intervention searches on ClinicalTrials.gov, deduplicate results
3Trial CharacterizationBatch-fetch eligibility, interventions, locations, status, descriptions for candidate NCT IDs
4Molecular Eligibility MatchingParse eligibility text for biomarker requirements, score patient-trial molecular match (0-40)
5Drug-Biomarker AlignmentIdentify trial drug mechanisms via OpenTargets/ChEMBL, verify target overlap with patient biomarkers
6Evidence AssessmentFDA approval, PubMed literature, CIViC evidence, evidence tier classification (T1-T4)
7Geographic & FeasibilityTrial site locations, enrollment status, proximity to patient location
8Alternative OptionsBasket/tumor-agnostic trials, expanded access, compassionate use programs
9Scoring & RankingCalculate Trial Match Score (0-100), assign tier, rank trials
10Report SynthesisGenerate markdown report with executive summary, ranked trials, evidence grading, checklist

Detailed phase execution code and tool call examples: see references/phases_detail.md

Trial Match Score (0-100)

Show full SKILL.md (442 more words)Show less
Score Components
ComponentMax PointsKey Criteria
Molecular Match40Exact variant match=40, Gene-level=30, Pathway=20, No criteria=10, Excluded=0
Clinical Eligibility25All criteria met=25, Most=18, Some=10, Ineligible=0
Evidence Strength20FDA-approved (T1)=20, Phase III (T2)=15, Phase II (T3)=10, Phase I (T4)=5
Trial Phase10Phase III=10, Phase II=8, Phase I/II=6, Phase I=4
Geographic Feasibility5Patient's city=5, Same country=3, International=1, Unknown=0
Recommendation Tiers
ScoreTierLabelAction
80-100Tier 1Optimal MatchStrongly recommend - contact site immediately
60-79Tier 2Good MatchRecommend - discuss with care team
40-59Tier 3Possible MatchConsider - needs further eligibility review
0-39Tier 4ExploratoryBackup option - consider if Tier 1-3 unavailable

Detailed scoring rules, evidence tier definitions, and matching algorithms: see references/scoring_and_matching.md

Output Format

Report file: clinical_trial_matching_[DISEASE]_[BIOMARKER]_[DATE].md

Required Sections
  1. Executive Summary - Top 3 trial recommendations with scores
  2. Patient Profile Summary - Standardized disease/biomarker/stage table
  3. Ranked Trial Matches - Per-trial score breakdown, eligibility, evidence, locations
  4. Trials by Category - Targeted/Immuno/Combination/Basket groupings
  5. Additional Testing Recommendations - Biomarkers that unlock more trials
  6. Alternative Options - Expanded access, off-label options
  7. Evidence Grading Summary - T1-T4 counts
  8. Completeness Checklist - Analysis step status tracking
  9. Disclaimer - Research-only notice
  10. Sources - Data source list

Full report template with markdown structure: see references/phases_detail.md#phase-10-report-synthesis

Edge Cases & Common Pitfalls

  1. ClinicalTrials.gov query complexity - Overly specific queries often return zero results. Start simple, then combine.
  2. CIViC search limitations - civic_search_variants/civic_search_evidence_items do NOT filter by query. Use civic_get_variants_by_gene with gene ID instead.
  3. No matching trials - Broaden to gene-level → pathway-level → basket trials → suggest biomarker testing.
  4. Rare biomarkers - Search gene-level trials, check CIViC, note rarity, suggest molecular tumor board.
  5. Multiple biomarkers - Search independently + in combination, score by most actionable.
  6. Conflicting eligibility - Score partial match transparently, highlight met/unmet criteria.

Full edge case handling and use patterns: see references/parsing_and_validation.md

Known CIViC Gene IDs

GeneCIViC IDGeneCIViC ID
ALK1MET52
ABL14PIK3CA37
BRAF5ROS1118
EGFR19RET122
ERBB220NTRK1197
KRAS30NTRK2560
TP5345NTRK3561

Input Validation

This skill accepts requests that match the documented purpose of tooluniverse-clinical-trial-matching and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

tooluniverse-clinical-trial-matching only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

FileContent
references/phases_detail.mdPhase 0-10 detailed execution code, tool call examples, parameter tables, report template
references/scoring_and_matching.mdScoring algorithm details, drug-biomarker alignment rules, evidence tier classification, matching logic
references/parsing_and_validation.mdBiomarker parsing regex, eligibility text parsing, gene resolution code, edge case handling, common use patterns

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in scientific-skills/Evidence Insight/tooluniverse-clinical-trial-matching of aipoch/medical-research-skills.

  • SKILL.md
  • EXAMPLES.md
  • POLISH_CHANGELOG.md
  • QUICK_START.md
  • TOOLS_REFERENCE.md
  • eval_report_tooluniverse-clinical-trial-matching_result.json
  • references/parsing_and_validation.md
  • references/phases_detail.md
  • references/scoring_and_matching.md

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Tooluniverse Clinical Trial Matching next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tooluniverse Clinical Trial Matching compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tooluniverse Clinical Trial Matching this skillaipoch/medical-research-skills1.9k—~2.6kAutomated safety check: PassMIT
Clinical Trials Databasegoogle-deepmind/science-skills3.2k2 repos~3.2kAutomated safety check: PassApache-2.0
CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw6171 repos~1.8kAutomated safety check: PassNone
Biomedical Analysis Dispatchxjtulyc/MedgeClaw6171 repos~2kAutomated safety check: PassNone
Research Paperluwill/research-skills862—~1.9kAutomated safety check: PassNone
Research Proposalluwill/research-skills862—~4.5kAutomated safety check: NotesNone

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Categories

Questions about Tooluniverse Clinical Trial Matching

What does Tooluniverse Clinical Trial Matching do?

AI-driven patient-to-trial matching for precision medicine and oncology. Tooluniverse Clinical Trial Matching is an agent skill from aipoch/medical-research-skills. AI-driven patient-to-trial matching for precision medicine and oncology.

When should I use Tooluniverse Clinical Trial Matching?

Tooluniverse Clinical Trial Matching fits situations like: tasks that involve Clinical and healthcare research.

How do I install Tooluniverse Clinical Trial Matching in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill tooluniverse-clinical-trial-matching -a claude-code`. Or copy the skill folder (scientific-skills/Evidence Insight/tooluniverse-clinical-trial-matching in aipoch/medical-research-skills) into .claude/skills/tooluniverse-clinical-trial-matching in your project. Claude Code loads it when a task matches its description.

How do I install Tooluniverse Clinical Trial Matching in Codex?

Run `npx skills add aipoch/medical-research-skills --skill tooluniverse-clinical-trial-matching -a codex`. Or copy the skill folder (scientific-skills/Evidence Insight/tooluniverse-clinical-trial-matching in aipoch/medical-research-skills) into .agents/skills/tooluniverse-clinical-trial-matching in your project. Codex loads it when a task matches its description.

Can I use Tooluniverse Clinical Trial Matching in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill tooluniverse-clinical-trial-matching -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tooluniverse-clinical-trial-matching, .gemini/skills/tooluniverse-clinical-trial-matching, .github/skills/tooluniverse-clinical-trial-matching and .opencode/skills/tooluniverse-clinical-trial-matching in your project.

What does Tooluniverse Clinical Trial Matching need to run?

SKILL.md names no scripts, command-line tools or credentials: Tooluniverse Clinical Trial Matching is instructions for the agent only.

Does Tooluniverse Clinical Trial Matching access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tooluniverse Clinical Trial Matching safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tooluniverse Clinical Trial Matching use?

Tooluniverse Clinical Trial Matching is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tooluniverse Clinical Trial Matching use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.

What are the alternatives to Tooluniverse Clinical Trial Matching?

Skills that share tags, products or a category with Tooluniverse Clinical Trial Matching: Clinical Trials Database (google-deepmind/science-skills, 3.2k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars) and Research Paper (luwill/research-skills, 862 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tooluniverse Clinical Trial Matching?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,937 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.