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mapping-loinc

Maps laboratory and clinical observation names extracted by OpenMed to LOINC codes using the public Regenstrief LOINC and FHIR terminology APIs. Use when the user wants to code lab tests, vital signs, or observations to LOINC, resolve a test name plus specimen and method to the correct LOINC part-model code, attach UCUM units, or build a US Core Laboratory Result Observation. Trigger keywords: LOINC, lab coding, observation code, UCUM units, specimen, method, US Core lab, FHIR Observation, lab result mapping, panel vs analyte. Pairs after OpenMed NER: consume Disease/Chemical/lab-name entities from openmed.analyze_text and map each measurement to a LOINC code. LOINC is free to use under the Regenstrief license (registration/terms-of-use, no fee); UMLS/SNOMED stay user-supplied and out-of-process.

74

Quality

91%

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SecuritybySnyk

High

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Actionable, executable body with a clear workflow and external references; slightly verbose in concept framing and licensing detail, and missing an explicit validate-fail-retry feedback loop for the batch case.

Suggestions

Trim the opening six-axis model explanation and deduplicate the licensing terms-of-use detail (covered both in the 'Quick start' area and the edge-cases section) to tighten token use.

Add an explicit feedback loop to the workflow: if $validate-code fails or $expand returns no good match, re-run the search with adjusted specimen/method axes rather than proceeding.

Consider moving the edge-cases/gotchas block into a references file so SKILL.md stays a lean overview, and reference it one level deep.

DimensionReasoningScore

Conciseness

Mostly efficient with executable code earning its place, but the opening framing of the six-axis LOINC model and the licensing detail repeated in both the body and the edge-cases section are minor instances of over-explanation that could be trimmed.

4 / 5

Actionability

Fully executable copy-paste-ready Python for $lookup, $validate-code, $expand, and the OpenMed hand-off, with a real example call (lookup("2823-3")) and concrete params/auth, covering the common cases.

5 / 5

Workflow Clarity

A clear numbered 6-step sequence with an explicit validation checkpoint ($validate-code then $lookup), but the batch-mapping flow lacks an explicit error-recovery/feedback loop when validation fails.

4 / 5

Progressive Disclosure

Well-organized sections with external reference URLs cleanly collected in a References section and no nested file references, but some inline density (repeated licensing, edge-cases) is a bit heavier than a pure overview.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, complete description: concrete capabilities, explicit 'Use when' trigger guidance, comprehensive natural keywords, and a clear niche that avoids conflicts with sibling coding skills.

DimensionReasoningScore

Specificity

Multiple concrete actions are enumerated — 'Maps...to LOINC codes', 'code lab tests, vital signs, or observations', 'resolve a test name plus specimen and method to the correct LOINC part-model code', 'attach UCUM units', 'build a US Core Laboratory Result Observation' — covering the task comprehensively in third person.

5 / 5

Completeness

It clearly states what the skill does (maps lab/observation names to LOINC via Regenstrief/FHIR APIs) and includes an explicit 'Use when the user wants to code lab tests, vital signs, or observations to LOINC...' clause with concrete trigger phrases.

5 / 5

Trigger Term Quality

An explicit 'Trigger keywords:' list gives comprehensive natural terms (LOINC, lab coding, observation code, UCUM units, specimen, method, US Core lab, FHIR Observation, lab result mapping, panel vs analyte) that users would naturally say.

5 / 5

Distinctiveness Conflict Risk

The LOINC lab-observation-coding niche is clearly distinguished from diagnoses (ICD-10), drugs (RxNorm), and SNOMED/UMLS, with distinct triggers and minimal overlap risk.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
maziyarpanahi/openmed
Reviewed

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