Skill UI

Performs pattern-driven searches for similar vulnerabilities across repositories after a known issue is found, guiding analysts through precise generalization, triage, and tool choices (ripgrep, Semgrep, CodeQL) to audit and prioritize true positives.

This skill simulates a senior documentation engineer, generating highly structured, evidence-based technical documentation. It processes codebases to create comprehensive wiki pages, mandating deep structural analysis, citing specific code paths (file:line), and incorporating mandatory architectural diagrams (Mermaid). Ideal for creating deep-dive system manuals, component guides, and technical deep dives with verifiable sources.

This skill simulates an expert software engineer and systems analyst. It is designed for deep, evidence-based understanding of complex codebases. Users can ask "how does X work" or request architectural reviews, ensuring every claim is grounded in actual code paths, data flows, and dependency chains, following a rigorous multi-iteration process.

This skill enables AI-assisted debugging and comprehensive error analysis within the development environment. It utilizes Cascade to analyze complex error messages, stack traces, and surrounding code context to identify root causes. Use it when troubleshooting code or encountering runtime errors to receive detailed fix recommendations and prevention strategies.

A comprehensive runbook for handling critical incidents related to Windsurf AI features, service outages, or production bugs caused by generated code. It guides teams through triage, mitigation (including Git reverting), root cause analysis, and post-incident reporting to ensure rapid recovery and process improvement.

ZAI CLI provides comprehensive access to Z.AI's advanced capabilities, including image/video analysis, real-time web search, web page extraction, and GitHub code exploration. It is designed for users needing multi-modal content analysis, error diagnosis, and complex data processing through a unified command-line interface. Ideal for developers and analysts requiring robust, API-driven AI functionality.

Seaborn is a powerful Python library for creating publication-quality statistical graphics. It is designed for dataset-oriented plotting, making it ideal for exploratory data analysis, multivariate analysis, and visualizing complex relationships, distributions, and comparisons with minimal code. It builds upon Matplotlib, offering high-level interfaces for functions like scatterplots, heatmaps, and pair plots.

A comprehensive toolkit for navigating, optimizing, and managing large monorepos built with JavaScript/TypeScript. It supports industry-leading tools like Turborepo, Nx, pnpm, and Lerna. Key features include cross-package impact analysis, selective builds, remote caching, dependency graph visualization, and structured migrations, ensuring fast, reliable CI/CD pipelines for complex codebases.

A powerful skill for conducting structured, systematic code reviews for PRs and MRs. It goes beyond basic style checks, performing deep analysis such as blast radius tracing, comprehensive security scanning (SQLi, XSS, secrets), detecting breaking changes in APIs/DB schemas, and calculating test coverage delta. Ideal for reviewing large, complex, or security-sensitive code changes before merging.

This skill establishes a rigorous framework for building deep architectural context by performing ultra-granular, line-by-line analysis of code. It applies methodologies like First Principles and 5 Whys to maintain a stable, evolving mental model of the entire system, making it essential for pre-vulnerability security auditing, threat modeling, and complex architecture reviews.

This skill provides deep technical expertise regarding the DWARF debugging format (v3-v5) and the DWARF standard. It assists in analyzing, parsing, verifying, and generating debug information from compiled binaries. Use cases include answering questions about the DWARF specification, writing code that interacts with DWARF data, and utilizing tools like `dwarfdump` or `readelf` for structural validation and quality metric extraction.

This skill provides a structured workflow for porting existing Semgrep security rules to multiple target languages. It guides users through applicability analysis, test-first rule creation, and validation for each language variant, ensuring consistent and accurate security coverage across polyglot codebases.