Skill UI

This skill converts unstructured documents (PDF, EPUB, DOCX, etc.) into actionable, structured agent skills. Instead of providing simple summaries, it deep-dives to extract core frameworks, mental models, key principles, techniques, and anti-patterns from educational material. Use this when you need to transform academic knowledge into a reusable, machine-readable toolkit for agents like Copilot CLI, Amp, or Claude Code.

This module provides a lazy adapter registry to seamlessly integrate OpenMed's clinical PII detection with major NLP frameworks like Microsoft Presidio, spaCy, and LangChain. It allows users to use OpenMed for enhanced PII recall, merge spans, or implement on-device PHI redaction guardrails without rewriting entire pipelines.

This tool provides a unified interface to run test suites for various programming stacks (Python, Node.js, Rust) within a CI/CD pipeline. It automatically detects the project's environment (by checking lock files or config) and executes the appropriate testing framework (e.g., pytest, vitest, cargo test), ensuring consistent code quality checks regardless of the underlying language. Ideal for pre-commit or CI/CD integration.

A specialized tool designed to detect, suggest, and evaluate Gang of Four (GoF) design patterns within TypeScript and JavaScript codebases. It analyzes code structure, identifies code smells, and provides stack-aware refactoring recommendations, supporting frameworks like React, Angular, NestJS, and Vue.

This guide provides a systematic framework for authorized email security reviews. It covers advanced phishing analysis, including deep dives into email headers, assessing SPF/DKIM/DMARC compliance, identifying Business Email Compromise (BEC) patterns, and researching mailbox token abuse. It is essential for incident response, threat intelligence, and security architecture review.

This tool analyzes specified source code files or modules to automatically generate comprehensive and structured test suites. It identifies testable units (functions, classes, methods), adheres to project conventions (like AAA pattern), and ensures high coverage for critical scenarios, including happy paths, boundary edge cases, and error handling. It supports popular frameworks such as Jest, Vitest, and pytest.

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 framework for authorized security assessments of Operational Technology (OT) and Industrial Control Systems (ICS). It emphasizes a 'passive-first' approach, covering Purdue model zoning, analyzing industrial protocols (Modbus, DNP3, etc.), and identifying exposure points on SCADA/DCS environments. The methodology strictly avoids disruptive write operations on PLCs, prioritizing read-only validation and safe network analysis for physical safety.

A comprehensive, multi-step framework for conducting systematic QA testing on web applications. This guide covers scope detection (diff-aware), tiered testing depth (Quick, Standard, Exhaustive), detailed issue taxonomy (Functional, Visual, UX, etc.), structured bug documentation, and the critical fix-and-verify loop, ensuring high code quality throughout the development cycle.

A specialized framework for conducting non-Wi-Fi RF/SDR security research in controlled, authorized laboratory environments. Focuses on passive signal identification, protocol analysis (e.g., remote controls, ADS-B), and feasibility studies. Emphasizes strict legal compliance, requiring analysis to be performed only in shielded labs with explicit authorization, and defaults to receiving-only mode.

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.

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.