Skill UI

This skill is designed for deep security and behavioral analysis within the Kubernetes control plane. It specializes in tracing complex interactions, including RBAC edge cases, service-account trust paths, admission webhook behavior, resource mutation, and cluster-level state drift. Use it when diagnosing why live workloads differ from manifest declarations, or when investigating cluster-wide permission issues.

Converts raw OpenMed NER outputs (text spans) into structured, standards-compliant FHIR R4 resources (e.g., Condition, Observation, MedicationStatement). It provides mechanical helpers for building CodeableConcepts using major coding systems like SNOMED, LOINC, and ICD-10, ensuring high interoperability with EHR systems and registries.

This utility separates clinical entity extraction from clinical coding. It processes de-identified text, utilizing OpenMed to identify key clinical spans. These spans are then programmatically mapped into structured FHIR R4 resources (like Condition, Observation, and MedicationStatement) and assembled into a Bundle. This process ensures deterministic, standardized data output suitable for interoperability and medical record structuring.

This skill automatically detects and extracts tabular laboratory panels from diverse sources, including scanned images, photos, and delimited files (CSV/TSV). It converts complex visual data into clean, structured rows, capturing the test name, measured value, unit, reference range, and abnormal flag. It is essential for preparing medical data for subsequent standardization using LOINC and UCUM, and for mapping into FHIR resources.

This skill facilitates the ingestion of unstructured clinical notes and reports from FHIR R4 EHR APIs (e.g., Epic, Cerner). It handles complex tasks including paginating large search results, decoding base64 attachments (PDF, text), and extracting narrative content. The extracted text is then passed to the OpenMed pipeline for HIPAA-compliant de-identification and subsequent NLP analysis, enabling structured data insights from raw clinical records.

This skill standardizes free-text medication mentions extracted by OpenMed to RxNorm RxCUIs using the public RxNav API. It resolves complex relationships between brand names, generic ingredients, strengths, and dose forms, providing a stable, canonical code. Ideal for clinical interoperability, data analytics, de-duplication, and building US Core Medication resources.