trialgpt-matching

trialgpt-matching，来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。

读凭据写文件读文件执行命令联网严重 0 · 高危 6FreedomIntelligence/OpenClaw-Medical-Skills

它会碰到什么

扫了多少16 个文本文件，778 KB

它会碰到什么读凭据写文件读文件执行命令联网

命中总数21 处

命中统计严重 0 · 高 6 · 中 12 · 低 0

逐条看命中（6 条严重或高危）

高 repo/trialgpt_matching/TrialGPT.py:26cred-envread
```
azure_endpoint=os.getenv("OPENAI_ENDPOINT"),
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高 repo/trialgpt_matching/TrialGPT.py:27cred-envread
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api_key=os.getenv("OPENAI_API_KEY"),
```
高 repo/trialgpt_ranking/TrialGPT.py:26cred-envread
```
azure_endpoint=os.getenv("OPENAI_ENDPOINT"),
```
高 repo/trialgpt_ranking/TrialGPT.py:27cred-envread
```
api_key=os.getenv("OPENAI_API_KEY"),
```
高 repo/trialgpt_retrieval/keyword_generation.py:25cred-envread
```
azure_endpoint=os.getenv("OPENAI_ENDPOINT"),
```
高 repo/trialgpt_retrieval/keyword_generation.py:26cred-envread
```
api_key=os.getenv("OPENAI_API_KEY"),
```

这一栏是扫描器报的事实，不是结论。命中多不等于有毒（安全工具、规则库、示例脚本本来就会包含危险写法），命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系，需要你自己看。

技能内容

<!--

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: 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.

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它属于哪个仓库

仓库FreedomIntelligence/OpenClaw-Medical-Skills

星标★ 3,010

本站分层T1

该仓技能数897

原文件路径skills/trialgpt-matching/SKILL.md

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