segmenting-clinical-sections SKILL.md skillA
segmenting-clinical-sections 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/segmenting-clinical-sections@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/segmenting-clinical-sections/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0, committed Jul 20, 2026
- Size
- 7,071 bytes
- Repository stars
- 5,784
- License
- Apache-2.0
Split a clinical note into canonical sections (Chief Complaint, HPI, PMH, Medications, Allergies, Assessment & Plan, etc.) before running OpenMed NER or de-identification, so section context sharpens downstream precision. Use when the user has a free-text note or discharge summary and wants section-aware processing, header detection, mapping headers to LOINC document-section codes, or per-section NER/de-id. Covers heuristic header detection, normalization to canonical section labels…
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
# Segmenting clinical sections A clinical note is not flat text — it is a sequence of named sections (Chief Complaint, HPI, Past Medical History, Medications, Allergies, Assessment & Plan). The **same phrase means different things in different sections**: "diabetes" in PMH is historical context, "diabetes" in Assessment & Plan is an active problem, and "penicillin" under Allergies is an adverse-reaction flag, not a current medication. Splitting the note into canonical sections **before** NER or de-identification gives every downstream OpenMed step the context it needs to be more precise — and lets you process sensitive sections under stricter policies. ## When to use - You have a free-text note, H&P, progress note, or discharge summary and are about to run NER (`extracting-clinical-entities`) or de-identification. - The user wants section detection, header parsing, LOINC section mapping, or per-section processing (e.g. "redact the Social History section harder"). - Downstream NER is over- or under-firing because it can't tell historical PMH mentions from active A&P problems. ## Quick start ```python import re import openmed # Synthetic note. …
Read the whole file at its exact version.
How to install
mdr add maziyarpanahi/openmed/segmenting-clinical-sections@sha256:337385f4bd62dd3aThe 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_yihzy54h3yxymmv4)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Jul 20, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (7071 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
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_yihzy54h3yxymmv4 GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/segmenting-clinical-sections GET https://markdownregistry.com/api/v1/blob/337385f4bd62dd3a8379f324616e6f04f21c2a8da2e0d1392f208af301cd9ba2
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.