Skill UI

This skill generates a comprehensive, structured threat model for any given service or feature using the STRIDE framework. It guides users through identifying critical assets, defining trust boundaries, enumerating specific threats (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege), assessing risk, and proposing concrete mitigation controls. Ideal for security design reviews and documentation.

This skill generates formal, audit-ready Standard Operating Procedures (SOPs) suitable for regulated industries, ISO certification, or internal process standardization. It structures the document with defined sections including Purpose, Scope, Definitions, Responsibilities, detailed Step-by-step Procedures, Quality Checks, and Non-Conformance handling, ensuring compliance and clarity for operational scaling.

This skill generates a comprehensive technical debt register for any team or service. It guides users to input critical data points (e.g., business impact, effort, tech stack) and produces a structured report that categorizes debt (Architecture, Security, Testing, etc.). The output includes a calculated priority score and a quarterly debt reduction roadmap, enabling deliberate, business-aware engineering decision-making.

A comprehensive template designed to structure complex technical specifications, ensuring a complete record of engineering decisions. It guides users to document problem statements, proposed solutions, system architecture, data models, API designs, security considerations, and rollout plans, bridging product requirements and technical implementation.

This skill generates a comprehensive and structured test strategy document. Given a feature specification, PRD, or system description, it systematically outlines the test scope, performs a detailed risk assessment, defines necessary test types (Unit, E2E, Performance, Security), and provides a prioritized, actionable test case outline to ensure robust quality assurance before release.

An adversarial Quality Assurance (QA) pass designed to deep-dive into any codebase for logic errors, security flaws, and functional bugs. Instead of confirming that code 'looks right,' this skill actively attempts to break the code by simulating hostile inputs, tracing critical data paths, and checking for subtle, real-world correctness issues. Essential for high-stakes, critical code reviews.

This meta-skill provides a comprehensive framework for the entire lifecycle of AI agent skills. It supports creating, refactoring, rigorously evaluating (e.g., Skill OS 2.0 Gates), and securely packaging skills from various sources like workflows, prompts, and documents. It ensures standardized, team-ready, and governed deployment of advanced AI capabilities.

A comprehensive, pre-deployment, defense-in-depth security audit tool for Solidity smart contracts built with Foundry. It combines static analysis (Slither, Aderyn), symbolic execution (Mythril), property-based fuzz testing, and key hygiene checks to proactively detect critical vulnerabilities like reentrancy, access control flaws, and arithmetic bugs before deployment to any EVM chain.

This skill provides a structured approach to monitoring and analyzing data leak sites (DLS) maintained by ransomware groups. By extracting structured data on victim postings, threat group tactics, and sector-specific details, users can assess current ransomware risk, track attack trends, and proactively build robust defense strategies.

This skill provides a comprehensive solution for monitoring brand impersonation attacks across multiple digital vectors. It systematically scans domains, social media platforms, mobile app stores, and the dark web to detect phishing campaigns, typosquatting, and unauthorized brand usage. It is essential for security teams conducting proactive threat intelligence gathering and vulnerability assessments to safeguard brand integrity.

This skill automates the entire phishing incident response workflow using the Splunk SOAR REST API. It parses suspicious email headers and bodies to extract artifacts (URLs, IPs, sender details), creates a structured incident container, triggers a comprehensive automated investigation playbook, and compiles a final verdict report for security teams.

This guide outlines a comprehensive workflow for detecting and preventing the exposure of sensitive AWS credentials (access keys, session tokens) within source code repositories, CI/CD pipelines, and configuration files. It utilizes TruffleHog for deep historical scanning and integrates git-secrets for robust pre-commit hooks, significantly reducing the risk of credential theft and unauthorized account access.