Skill UI

Analyzes a codebase to surface subdomains (Core, Supporting, Generic) and recommend bounded contexts using DDD strategic design, helping teams clarify domain boundaries, cohesion, and service split decisions.

Scans your codebase with pattern matching and entropy analysis to detect exposed secrets like API keys, passwords, and private keys, then generates remediation reports so you can fix vulnerabilities before committing or deploying code.

Runs Semgrep static analysis with auto language detection, parallel Task subagents, Semgrep Pro checks, and configurable “run all” or “important only” modes to audit codebases for vulnerabilities and bug patterns.

A comprehensive skill to identify, analyze, prioritize, and track technical debt across large codebases. It provides three interconnected tools: a Debt Scanner, a Debt Prioritizer (using cost-of-delay frameworks), and a Debt Dashboard. This system helps engineering teams make data-driven decisions to balance new features with necessary maintenance and refactoring work, ensuring the long-term sustainability of software systems.

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.

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.

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.

A systematic skill for identifying similar vulnerabilities and bugs across large, complex codebases. It guides the user through generalizing initial bug patterns using techniques like CodeQL and Semgrep, ensuring comprehensive security audits beyond the initially discovered flaw. Ideal for advanced security research and robust code auditing.

A forensic tool for performing post-mortem analysis on AI-assisted coding sessions. It goes beyond simply stating what was done, determining *why* work deviated (e.g., spec ambiguity, repo friction, agent error), identifying scope creep, and classifying rework patterns. It provides evidence-backed recommendations to improve prompts, codebase health, and future development workflows.

A comprehensive set of specialized tools for deep interaction with source codebases. This context-mode is mandatory for advanced tasks such as running code snippets, analyzing files, batch processing repository commands, indexing knowledge, searching content, and fetching web data. It ensures that interactions are context-aware and highly efficient, moving beyond basic file listing or general chat prompts.

A comprehensive guide and toolset for Go code quality assurance using `golangci-lint`. It enables developers to run multiple linters in parallel, configure best practices via `.golangci.yml`, automate fixes, and interpret complex lint output. Ideal for maintaining code standards, setting up CI/CD pipelines, and cleaning up legacy codebases.