Skill UI

A comprehensive, multi-phase security scanner designed to audit development environments (Claude Code setup). It checks MCP servers, installed skills, agents, and hooks against known threat databases, malicious patterns, and supply chain vulnerabilities. Key checks include CVE screening, prompt injection detection, and unauthorized network access patterns.

This technique segments unstructured clinical documents (such as HPI, PMH, and A&P sections) into contextually rich, canonical chunks. This is crucial for improving the precision of downstream NLP tasks like Named Entity Recognition (NER) and de-identification. By identifying and normalizing headers and mapping them to LOINC codes, the system ensures that the source context (e.g., historical vs. active) is maintained, leading to significantly more accurate results.

Provides a hardened FastAPI endpoint for OpenMed's core functionalities: clinical Named Entity Recognition (NER), Personally Identifiable Information (PII) extraction, and de-identification. Designed for self-hosted microservices, it handles inference requests, model lifecycle management, and supports dynamic batching, ensuring secure, on-device processing of sensitive clinical data.

The Ship command provides a comprehensive, multi-stage checklist for ensuring code readiness before production deployment. It verifies critical quality gates, including running full unit tests, performing security audits, checking for hardcoded secrets, and verifying documentation updates. Use this tool to guarantee the stability and quality of every software release.

This skill converts free-text radiology narratives (CT, MRI, X-ray, etc.) into structured, machine-readable data. It automatically identifies and segments key report sections (Technique, Findings, Impression) and extracts critical clinical details such as anatomy, measurements, laterality, BI-RADS/Lung-RADS scores, and follow-up recommendations. It is crucial for building structured medical records and decision support systems.

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 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.

Provides a comprehensive framework for blue-team threat hunting and detection engineering. Users learn hypothesis-driven hunting techniques, optimize SIEM queries, and build robust detection rules using industry standards like Sigma and YARA. Essential for minimizing false positives and validating security controls in a defensive posture.

This skill manages the complex, multi-step workflow for updating the company's threat intelligence database. It delegates the core research and content updates to the dedicated AgentSec system. The process involves reading AgentSec's source material, executing rigorous testing in an isolated workspace, synchronizing the validated security feed, and finally ensuring data integrity by validating the updates across the guide and landing mirrors.

This tool leverages an LLM-as-a-Judge agent to thoroughly evaluate staged Git changes before they are committed. It checks for correctness, completeness, and safety issues, providing a detailed verdict (APPROVE, NEEDS_REVIEW, REJECT) and actionable feedback. It is essential for maintaining high code quality, especially in complex or security-sensitive code sections.

This skill processes verbose, stream-of-consciousness voice dictations (from tools like macOS Dictation or Wispr Flow) and transforms them into highly structured, token-efficient prompts. It removes filler words, repetitions, and tangents, organizing the core intent into standard sections (Context, Objective, Constraints) suitable for advanced LLMs like Claude Code.

This guide outlines a structured methodology for authorized wireless security assessments. It covers essential techniques such as Wi-Fi data capture, WPA/WPA2 handshake analysis, and rogue Access Point detection. It is designed for assessing corporate network security, verifying wireless isolation, and providing professional penetration testing recommendations, strictly adhering to legal scope and authorization.