resolving-clinical-context SKILL.md skillA

resolving-clinical-context from maziyarpanahi/openmed is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add maziyarpanahi/openmed/resolving-clinical-context@v1.0

Pins 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/resolving-clinical-context/SKILL.md
Versions recorded
1
Latest version
v1.0, committed Jul 20, 2026
Size
7,079 bytes
Repository stars
5,784
License
Apache-2.0

Assign negation, temporality, and uncertainty (the ConText axes) to clinical entities extracted by OpenMed, so "denies chest pain" is not counted as chest pain and "history of MI" is not counted as an active MI. Use after NER when the user needs assertion status, negation detection, family-history / hypothetical / historical flags, or ConText/NegEx-style classification before grounding entities to FHIR or a problem list. Covers openmed.clinical.resolve_negation / resolve_temporality /…

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

# Resolving clinical context

NER finds *that* a condition was mentioned; it does not tell you whether the
patient **has** it. "Patient denies chest pain," "history of MI," and "rule out
PE" all surface entities that must **not** be recorded as active, present
findings. OpenMed's `openmed.clinical` ConText layer assigns three deterministic
axes to each span — **negation**, **temporality**, **uncertainty** — turning raw
mentions into clinically faithful assertions before they reach a problem list or
FHIR Condition.

## When to use

- Immediately after `extracting-clinical-entities`, before grounding,
  problem-list building, or analytics.
- The user asks for assertion status, negation handling, "is this affirmed?",
  family-history vs. patient, historical vs. active, or hedged/uncertain findings.
- You are about to map entities to FHIR `verificationStatus` /`clinicalStatus`
  and need the upstream signal.

## Quick start

```python
import openmed
from openmed.clinical import (
    resolve_span_context, assert_context_axes,
    NEGATED, HISTORICAL, HYPOTHETICAL, UNCERTAIN,
)

note = "Patient denies chest pain. History of MI. Concern for PE; rule out DVT."
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add maziyarpanahi/openmed/resolving-clinical-context@sha256:707db6219f83a597

The 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.

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Versions

The registry has recorded 1 version of this file, committed on Jul 20, 2026.

versioncommittedcommitsizeaudit
v1.0 latest2026-07-20 74f7d6b 7,079 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (7079 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

GitHub

maziyarpanahi/openmed · 5,784 stars · license Apache-2.0 · pushed 2026-11-07 · branch master

API

GET https://markdownregistry.com/api/v1/artifacts/art_mea6bo33igp5kbep
GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/resolving-clinical-context
GET https://markdownregistry.com/api/v1/blob/707db6219f83a597c7aa8ac444c91029c502b8a234d4dafbe7d5f9fdfef754ad

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.

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