parsing-trial-eligibility SKILL.md skillA
parsing-trial-eligibility from maziyarpanahi/openmed is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add maziyarpanahi/openmed/parsing-trial-eligibility@v1.0Pins v1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- maziyarpanahi/openmed
- Path
skills/parsing-trial-eligibility/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0, committed Jul 20, 2026
- Size
- 8,257 bytes
- Repository stars
- 5,784
- License
- Apache-2.0
Parses free-text clinical-trial eligibility criteria into structured inclusion and exclusion logic, then matches them against patient facts that OpenMed extracted. Use when the user wants to turn a ClinicalTrials.gov eligibility block into machine-readable rules, screen a synthetic patient for trial fit, or explain why a patient does or does not meet criteria. Trigger keywords: eligibility criteria, inclusion, exclusion, trial matching, patient screening, criteria parsing, eligibilityModule…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Parsing trial eligibility & matching patients A ClinicalTrials.gov study exposes its eligibility as a single free-text block (`protocolSection.eligibilityModule.eligibilityCriteria`) plus a few typed fields (`sex`, `minimumAge`, `maximumAge`, `healthyVolunteers`). This skill turns that prose into **structured inclusion / exclusion criteria** and matches each rule against patient facts that **OpenMed** extracted — producing an explainable `eligible | ineligible | unknown` verdict per criterion. This is **decision support, not enrollment**. The output is a candidate list and a rationale for a clinician to review, never an automated eligibility decision. ## When to use - You pulled a study with `searching-clinicaltrials` and need its eligibility as machine-readable rules. - You have a (synthetic) patient profile and want to screen it against one or many trials, with a per-criterion reason. - You want to highlight which patient facts are missing to decide a criterion. ## Quick start The typed gates are deterministic — apply them first. The free-text criteria need parsing into bullet-level inclusion/exclusion items. ```python …
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How to install
mdr add maziyarpanahi/openmed/parsing-trial-eligibility@sha256:2fddebb4e829b92dThe line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_xv2me5jf7o6rklv3)
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Versions
The registry has recorded 1 version of this file, committed on Jul 20, 2026.
Audit of the latest version
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Source
maziyarpanahi/openmed · 5,784 stars · license Apache-2.0 · pushed 2026-11-07 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_xv2me5jf7o6rklv3 GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/parsing-trial-eligibility GET https://markdownregistry.com/api/v1/blob/2fddebb4e829b92d4bb350129e124527bccc49c9f036b763dae18503c8eda2ca
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