Skill UI

This skill parses standardized C-CDA/CCD XML clinical documents exported from EHRs. It extracts both human-readable section narrative text and coded entries, mapping them by LOINC codes and template IDs. It is essential for preparing clinical free-text data for subsequent NLP analysis and supports XML-aware de-identification while preserving document structure.

This skill facilitates the crucial grounding step for clinical coding by interacting with external FHIR terminology servers. It supports core operations such as `$validate-code`, `$expand` (for ValueSets), `$lookup`, and `$translate` (ConceptMaps). It ensures that raw text spans are converted into validated, coded `CodeableConcept` resources using industry standards like SNOMED CT, LOINC, and ICD-10, maintaining interoperability.

This skill processes raw mentions of conditions and diagnoses extracted from clinical notes. It performs synonym deduplication, filters out negated or hypothetical mentions, and assigns a structured clinical status (active, resolved, or historical). The output is a clean, reconciled problem list, structured for USCDI Problem or FHIR Condition elements.

This tool analyzes a given codebase to automatically identify high-value, actionable automation routines. It surfaces use cases across three primary trigger types: scheduled cron jobs, external API calls, and GitHub repository events. By mapping manual pain points to autonomous workflows, it helps teams implement robust CI/CD and DevOps practices.

A comprehensive framework for assessing software supply chain security. It covers generating Software Bill of Materials (SBOM), performing Software Composition Analysis (SCA) on open-source dependencies, auditing CI/CD pipelines, and analyzing container images. This skill helps identify vulnerabilities, ensure build integrity, and verify component provenance across the entire development lifecycle.

This skill validates FHIR R4 resources and Bundles against mandatory US Core profiles (USCDI). It goes beyond mere syntactic checks to ensure that data prepared for submission to major Electronic Health Records (EHRs) like Epic or Cerner meets the required US-specific conformance standards. It detects common data gaps, checks 'must-support' elements, and converts the comprehensive validation report into a standard FHIR OperationOutcome for seamless pipeline integration.