resolving-clinical-context
resolving-clinical-context is an NLP, speech & audio ML skill for AI agents, published by maziyarpanahi in the openmed repository on GitHub. Skillspace rates resolving-clinical-context C (74/100) and it passed the safety scan; the rating is based on static analysis only.
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 / resolve_uncertainty / resolve_span_context / assert_context_axes, ClinicalAssertion, and the AFFIRMED/NEGATED, RECENT/HISTORICAL/HYPOTHETICAL, CERTAIN/UNCERTAIN constants. Pairs after extracting-clinical-entities.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 4,654
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Uses OpenMed's public openmed.clinical ConText layer
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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