Reviewer-gated extraction skill for deriving L2 structured artifacts from ingested normalized sources. Runs MCP terminology enrichment, presents batch proposals for human review, records decisions via concept review CLI, and writes finalized `topics/<topic>/structured/concepts/concepts.yaml` plus an extract plan that includes an explicit `concepts` terminology artifact row. Supported modes: plan · implement · verify. Use when the user asks to extract structured artifacts from sources for a topic.
Reviewer-gated formalization skill for converging approved L2 structured artifacts into L3 FHIR computable resources. Uses type-specific strategies to map each L2 artifact type to its correct FHIR R4 targets. Modes: plan, implement, verify
Source preparation skill for the HI evidence pipeline. Normalizes all files in sources/ to Markdown, infers and initializes topics, classifies each source (using discovery-plan.yaml as optional enrichment when present), and annotates with concept metadata in normalized front matter for downstream extraction. Modes: plan, implement, verify
First-class CQL (Clinical Quality Language) authoring, review, debugging, and test-plan skill for the rh-skills informatics workflow.
Interactive conflict resolution guide for RH lifecycle plans. Iterates through all open concerns across extract-plan.yaml and formalize-plan.yaml, presents each to the human reviewer, records the resolution, and confirms the plan is clear before proceeding to implementation.
Unified topic-level verification orchestrator for the RH lifecycle. Read-only. Launches stage-specific verify workflows via subagents and returns one consolidated report. Modes: verify.
Use SNOMED CT's semantic attribute relationships to answer clinical questions. Finds concepts by relationship attribute (finding site, causative agent, associated morphology, procedure site), navigates the IS-A hierarchy, and composes property-filtered ValueSets. Use when the user asks things like "all disorders of the heart", "all procedures on the kidney", "all conditions caused by bacteria", "subtypes of hypertension", "symptoms of X", "complications of X", or any query that involves clinical relationships between concepts rather than simple text search.
Map a code from any clinical terminology (ICD-10-CM, LOINC, RxNorm) to its SNOMED CT equivalent in order to unlock SNOMED's rich semantic attribute relationships. Use when the user has a code in a non-SNOMED system and wants to explore related concepts, find clinically adjacent codes, understand the semantic meaning, or build a SNOMED-based ValueSet from a non-SNOMED starting point. Always propose this when a user asks about relationships or "what is related to X" and the code is not already in SNOMED.