install
source · Clone the upstream repo
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/trialgpt-matching" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-trialgpt-matching && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/trialgpt-matching" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-trialgpt-matching && rm -rf "$T"
manifest:
skills/trialgpt-matching/SKILL.mdsafety · automated scan (low risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
- pip install
Always read a skill's source content before installing. Patterns alone don't mean the skill is malicious — but they warrant attention.
source content
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
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:
(or reuse env).cd repo && pip install -r requirements.txt - 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
for criterion-level review.Skills/Clinical/Trial_Eligibility_Agent