Skill UI

This skill provides a comprehensive checklist for auditing de-identified Protected Health Information (PHI) against the 18 categories required by HIPAA Safe Harbor (45 CFR 164.514(b)(2)). It maps detected PII entities to these categories, identifies gaps (e.g., age > 89, rare geography), and guides the assessment of residual re-identification risk. This is essential for proving the completeness and compliance of de-identification efforts.

This skill audits OpenMed NER or de-identification models to detect performance disparities across sensitive demographic subgroups (e.g., sex, age, race). It calculates metrics like per-group recall and leakage disparity, helping users identify instances of 'under-protection' before deployment, ensuring equitable AI governance and compliance.

This tool benchmarks the recall of PII detection models, crucial for ensuring privacy compliance before deployment. It uses synthetic fixtures and enforces a recall floor by measuring label-aware exact-span and grapheme recall against predefined gold standards. It is essential for auditing models and preventing critical privacy leaks.

This guide provides a comprehensive methodology for the reverse engineering of browser extensions (Chrome/Firefox). It covers analyzing the manifest, tracing background workers, content scripts, and recovering sensitive logic like credentials or network traffic. Essential for security research, malware investigation, and supply chain security auditing.

This skill acts as a comprehensive map for developing clinical and biomedical NLP pipelines using OpenMed. OpenMed is a local-first Python library that performs named-entity recognition (NER), protected health information (PHI) de-identification, and FHIR export, all running fully on-device without cloud calls. Use this guide when starting a new clinical text project, needing to select the appropriate capability (e.g., zero-shot NER, auditing, or FHIR conversion), or requiring an entry point for the core OpenMed features.

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.

A specialized skill for analyzing and reproducing complex, timing-dependent bugs in concurrent systems. Use this to investigate race windows, ordering bugs, lock gaps, stale reads, or state inconsistencies where the final outcome depends critically on request timing or asynchronous execution order. Essential for deep security auditing and debugging of distributed transactions.

A comprehensive skill for AI agents to perform advanced filesystem operations. It provides features for intelligent file listing with deep filtering, powerful content and pattern searching, safe batch file copying, and detailed directory analysis (statistics, tree visualization). Ideal for code analysis, system auditing, and managing project assets.

A comprehensive framework for conducting authorized security assessments on Large Language Models (LLMs) and AI agents. It covers critical vulnerabilities including advanced prompt injection (OWASP Top 10), tool abuse, RAG data poisoning, memory manipulation, and system prompt extraction. Ideal for red teaming, security auditing, and ensuring the robustness of AI systems in production environments.

A comprehensive guide for auditing and polishing original long-form manuscripts intended for submission to high-level Pattern Recognition and AI journals. It details mandatory components, formatting standards, anti-plagiarism checks, and ethical guidelines, ensuring the paper meets rigorous peer-review standards for publication.

This skill facilitates reversible de-identification (pseudonymization) of clinical text, allowing sensitive Protected Health Information (PHI) to be masked for processing while retaining the ability to restore the original data later under strict authorization. It captures a mapping key and provides a function to re-identify the text, crucial for workflows like GDPR compliance, patient recontact, or auditing. Crucially, the re-identification mapping must be stored separately and securely.

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.