How do I install the Trialgpt Matching skill?

Run npx skillmds@latest add biotender-max/trialgpt-matching in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Trialgpt Matching skill do?

<!-- It is listed under Coding & Dev Tools on SkillMD.

Is Trialgpt Matching safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Trialgpt Matching?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Trialgpt Matching free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Trialgpt Matching?

BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Trialgpt Matching by biotender-max — Agent Skill

Name: Trialgpt Matching
Author: BioTender-max

File contents

name: trialgpt-matching description: Trial shortlist keywords: - retrieval - ranking - ClinicalTrials - patient-profile measurable_outcome: Produce ≥5 ranked trials (when available) with rationale + missing-data notes within 3 minutes of receiving a patient query. license: MIT metadata: author: TrialGPT Team version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - read_file

TrialGPT Matching

Run the locally checked-out TrialGPT pipeline to retrieve, rank, and explain candidate trials for a patient before deeper eligibility review.

Inputs

Patient summary (structured JSON or free text) with condition keywords.
Optional filters: geography, phase, intervention, biomarker.
Up-to-date ClinicalTrials.gov dump or API access.

Outputs

Ranked trial table with NCT ID, title, score, and short justification.
Parsed inclusion/exclusion text ready for downstream eligibility agents.
Missing data checklist (e.g., "ECOG not provided").

Workflow

Setup: cd repo && pip install -r requirements.txt (or reuse env).
Trial retrieval: Run TrialGPT retriever to pull candidate trials for the indication.
Criteria parsing: Convert eligibility blocks to structured criteria JSON.
Patient profiling: Summarize patient facts (labs, prior therapies, biomarkers).
Ranking: Execute TrialGPT ranking script to score each trial and emit explanations.
Handoff: Export ranked list + structured criteria for trial-eligibility-agent.

Guardrails

Refresh ClinicalTrials.gov metadata regularly to avoid stale trials.
Label scores as AI-generated suggestions pending clinician validation.
Retain prompt/config metadata for audit trails.

References

Detailed usage instructions and repo layout live in README.md.
Coordinate with Skills/Clinical/Trial_Eligibility_Agent for criterion-level review.

---name: trialgpt-matchingdescription: ---name: trialgpt-matchingdescription: Trial shortlistkeywords: - retrieval - ranking - ClinicalTrials - patient-profilemeasurable_outcome: Produce ≥5 ranked trials (when available) with rationale + missing-data notes within 3 minutes of receiving a patient query.license: MITmetadata: author: TrialGPT Team version: "1.0.0"compatibility: - system: Python 3.9+allowed-tools: - run_shell_command - read_file---# TrialGPT MatchingRun the locally checked-out TrialGPT pipeline to retrieve, rank, and explain candidate trials for a patient before deeper eligibility review.## Inputs- Patient summary (structured JSON or free text) with condition keywords.- Optional filters: geography, phase, intervention, biomarker.- Up-to-date ClinicalTrials.gov dump or API access.## Outputs- Ranked trial table with NCT ID, title, score, and short justification.- Parsed inclusion/exclusion text ready for downstream eligibility agents.- Missing data checklist (e.g., "ECOG not provided").## Workflow1. **Setup:** `cd repo && pip install -r requirements.txt` (or reuse env).2. **Trial retrieval:** Run TrialGPT retriever to pull candidate trials for the indication.3. **Criteria parsing:** Convert eligibility blocks to structured criteria JSON.4. **Patient profiling:** Summarize patient facts (labs, prior therapies, biomarkers).5. **Ranking:** Execute TrialGPT ranking script to score each trial and emit explanations.6. **Handoff:** Export ranked list + structured criteria for `trial-eligibility-agent`.## Guardrails- Refresh ClinicalTrials.gov metadata regularly to avoid stale trials.- Label scores as AI-generated suggestions pending clinician validation.- Retain prompt/config metadata for audit trails.## References- Detailed usage instructions and repo layout live in `README.md`.- Coordinate with `Skills/Clinical/Trial_Eligibility_Agent` for criterion-level review.

Frequently asked questions

Trialgpt Matching