Skill UI

Provides a structured reference covering the 100 most critical web vulnerabilities, including definitions, root causes, impacts, and mitigation guidance aligned with OWASP categories to support assessments and remediation planning.

A specialized assistant designed to act as a senior software architect. It critiques code generated by AI tools or rapidly prototyped code, moving beyond simple syntax checks. The auditor identifies deep structural flaws, technical debt, architectural weaknesses, and production risks (e.g., security vulnerabilities, poor error handling, tight coupling) that make code fragile or unsuitable for deployment.

A comprehensive security scanner designed to audit AI agent skills before deployment. It analyzes source code (Python, Bash, JS), detects critical vulnerabilities like command injection, network exfiltration, and unsafe deserialization. Furthermore, it scans markdown files for prompt injection attacks, and assesses dependency supply chain risks, providing a clear PASS/WARN/FAIL verdict and remediation guidance.

Performs static security analysis on GitHub Actions workflows that incorporate AI coding agents (e.g., Claude, Gemini, OpenAI). This skill helps identify critical data flow vulnerabilities, such as where attacker-controlled input can reach AI agent prompts or internal systems via CI/CD pipelines, going beyond simple expression checks.

This skill simulates a senior engineer's final, deep audit of an entire codebase before committing or pushing to a remote repository. It systematically checks for junk files, dead code, security vulnerabilities (secrets, injection flaws), and performance bottlenecks (N+1 queries). Use this pre-flight check before any major release or public deployment to ensure maximum code quality and production readiness.

A rigorous, security-focused code review process designed for Pull Requests (PRs), commits, and diffs. It moves beyond general reviews by focusing intensely on high-risk areas such as authentication, cryptography, external calls, and value transfer. The methodology is evidence-based, requiring detailed attack scenario modeling and generating comprehensive, auditable markdown reports to identify overlooked vulnerabilities and regressions.

A rigorous framework designed to audit GitHub Actions workflows for exploitable security vulnerabilities. This skill focuses strictly on real-world attack patterns, requiring every identified finding to include a concrete exploitation scenario (Entry Point, Payload, Impact). Ideal for securing CI/CD pipelines against external attackers.

Scans Go codebases for security vulnerabilities, highlighting risky patterns, insecure dependencies, and misconfigurations so auditors can catch issues before deployment.

Leverages Monte Carlo-based simulation to spot potential software vulnerabilities by feeding randomized inputs into modules, tracking failure likelihoods, and highlighting risky code paths for security testing.

Python Security Auditor is a concise tool that inspects Python codebases for common vulnerabilities and configuration issues, helping developers prioritize fixes and maintain secure deployments.

Automated Rust Security Auditor for analyzing crate source code to spot vulnerabilities, dependency issues, and unsafe patterns before deployment across teams.

This skill provides a comprehensive guide for creating production-quality custom Semgrep rules. It teaches best practices for detecting security vulnerabilities, enforcing robust coding standards, and identifying specific bug patterns. By emphasizing a test-first approach and utilizing advanced techniques like taint mode, users can write highly accurate static analysis rules that drastically reduce false positives.