Skill UI

This skill transforms raw genomic identifiers (VCF, HGVS, rsID) into highly annotated, consequence-predicted records. It utilizes powerful, open-source tools like Ensembl VEP and gnomAD to predict variant consequences (e.g., missense, nonsense), map coordinates, and attach population allele frequencies. Furthermore, it links these molecular findings to clinical and phenotype context extracted by OpenMed, forming a comprehensive research record.

This skill serves as a deterministic internal downloader for image URLs extracted from comprehensive web search results. It receives normalized media slots and search output via stdin, utilizing Python HTTP APIs to download direct image links. The process includes validating MIME types and saving files accurately into the configured local project directory, ensuring reliable asset retrieval without relying on sandboxed shell tools.

This skill scaffolds a gold-standard annotation project tailored for evaluating clinical NER and de-identification models (OpenMed). It guides users through defining label schemas, writing rigorous guidelines, configuring annotation tools (like BRAT/Label Studio), generating synthetic clinical text, and creating disciplined, non-leaking train/dev/test splits. It ensures that all committed data are synthetic fixtures for reproducible evaluation.

A comprehensive white-box security auditing workflow designed for proprietary source code. It integrates static analysis security testing (SAST) tools like Semgrep and CodeQL to detect common vulnerabilities (e.g., injection, IDOR, crypto misuse), followed by mandatory manual threat modeling and verification steps. Applicable for PR reviews and pre-deployment security checks.

This skill deploys the OpenMed Model Context Protocol (MCP) server, exposing critical clinical NLP tools such as NER, PII extraction, and de-identification. It enables AI coding agents and chat clients to interact with OpenMed's capabilities via simple tool calls, running locally on-device to ensure user data privacy and security. Supports both stdio and Streamable HTTP deployment modes.

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.

A comprehensive guide for performing reverse engineering using Ghidra. This skill is essential for scenarios where commercial tools like IDA are unavailable, or when performing large-scale, automated headless analysis. It covers the entire workflow, from project setup and function decompilation to advanced headless scripting and integration with other exploit tools.

A comprehensive, systematic workflow for reverse engineering client-side JavaScript. It guides users through five stages: Observation, Capture, Rebuilding, Patching, and Deep Dive. Applicable for locating API signatures, analyzing encryption parameters, tracking runtime function calls, and reconstructing complex web environments locally for evidence collection and reproduction. Utilizes advanced tools like jshookmcp and various js-reverse_* utilities.

This comprehensive guide details the methodology for reverse engineering macOS and Mach-O binaries. It covers analyzing application bundles, deciphering Objective-C/Swift symbols, examining code signing and hardened runtime features, and performing both static (using tools like Ghidra, IDA) and dynamic analysis (using lldb, Frida) to aid in malware analysis and platform security research.

This mode defines an autonomous, senior-level AI agent capable of resolving complex tasks from start to finish with minimal human supervision. It operates by strictly verifying every claim against real evidence (live web search, codebase, available tools). The agent prioritizes action over questioning, only interrupting the user for irreversible actions, genuine dead-ends, or critical ambiguities, ensuring maximum efficiency in hands-on engineering and operational workflows.

A comprehensive guide for embedding OpenMed-powered tools into Electronic Health Records (EHRs) like Epic or Cerner. It covers the entire SMART on FHIR workflow, including OAuth2 PKCE authorization, granular scoping (e.g., patient/DocumentReference.rs), secure token handling, and processing clinical notes locally on-device for de-identification and Named Entity Recognition (NER).

This comprehensive guide outlines a structured methodology for conducting authorized security testing on desktop thick clients (Win/macOS/Linux). It covers critical attack vectors, including local storage analysis, Inter-Process Communication (IPC) vulnerabilities, network traffic interception, client-side trust boundaries, and advanced reverse engineering techniques using tools like IDA and Ghidra.