Skill UI

Provides decision support for mapping diagnoses and procedures extracted by OpenMed to standardized ICD-10-CM and ICD-10-PCS codes. This skill suggests candidate codes along with detailed clinical rationale, helping human coders narrow down options, route findings to specific chapters, and pre-fill encounter records. Note that the output is advisory and requires mandatory validation by a certified medical coder.

A specialized downstream skill for CTF-sandbox workflows. Used to analyze complex security challenges driven by AI agent interactions, prompt injection, or infrastructure vulnerabilities. Focuses on tracing control chains involving untrusted input, tool side effects, deployment drift, container runtime issues, and CI/CD supply chain provenance. Ideal for rigorous vulnerability assessment in modern, distributed systems.

A highly specialized skill for advanced security analysis, designed to trace complex Kerberos delegation chains (including constrained, unconstrained, and RBCD). Use this skill to pinpoint the exact delegation edge, analyze ticket minting (S4U), and prove the effective privilege gained by a target service, going beyond simple domain compromise statements.

This advanced skill specializes in tracing the complete provenance of software artifacts across the entire development lifecycle. It is designed for deep security analysis of CI/CD pipelines, identifying dependency drift, build tampering, package origin, and determining the final artifact consumed at runtime. Use it when investigating integrity vulnerabilities in complex release flows.

This skill guides the creation of computable phenotypes and patient cohorts using the OHDSI/OMOP CDM standards. It allows users to define precise, executable criteria by combining standard concept sets (like PheKB) with advanced Natural Language Processing (NLP) features extracted from free clinical text. Use this when structured codes alone are insufficient to capture critical health information (e.g., symptoms, social context).

This skill performs the crucial ETL process of mapping OpenMed-extracted, terminology-coded clinical facts (conditions, drugs, measurements) into the OMOP Common Data Model (CDM) v5.4 tables. It is used downstream after entity extraction and source coding, transforming raw NLP findings into standardized, OMOP-conformant records for OHDSI analytics.

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 skill extracts crucial Social Determinants of Health (SDOH) — such as housing instability, food insecurity, and transportation barriers — from unstructured clinical notes. It maps the identified text spans to standardized ICD-10-CM Z-codes (Z55–Z65). It is essential for health-equity analytics, building risk stratification tools, and identifying coding gaps by converting narrative text into queryable, discrete data points.

Synthea generates statistically realistic, fully synthetic patient records in multiple standards (FHIR R4, C-CDA, CSV). This tool is essential for developers and researchers needing safe, shareable test data for OpenMed pipelines, CI fixtures, or specialized de-identification leakage gate test sets. It ensures zero risk of exposing real Protected Health Information (PHI).

This module converts diverse clinical inputs—including scanned images, faxes, CSV/TSV exports, and C-CDA XML—into a normalized, clean text format (`ExtractedDocument`). It supports on-device OCR (Tesseract/PaddleOCR) and structured redaction for tables. It is the crucial first stage for feeding de-identification and Named Entity Recognition (NER) pipelines.

This skill resolves entities extracted by OpenMed (e.g., Disease, Drug) to standardized Concept Unique Identifiers (CUIs) within the UMLS Metathesaurus. It is essential for cross-vocabulary normalization, allowing users to unify concepts (like SNOMED CT, ICD-10, RxNorm) to a single canonical CUI. Crucially, the process relies entirely on the user's own UTS API key, ensuring that the Metathesaurus content is never bundled or cached.

This skill maps clinical concept spans (disorders, anatomy, procedures, etc.) extracted by OpenMed to SNOMED CT concept IDs (SCTID). It performs complex, out-of-process terminology resolution using standard FHIR R4 endpoints ($lookup, $translate, ValueSet/$expand) against a user-supplied, licensed terminology server (e.g., Ontoserver, UTS). Ideal for generating rich, hierarchy-aware clinical codes, performing subsumption queries (ECL), or translating codes between clinical standards (like ICD-10 to SNOMED CT).