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Found 1,560 Skills
Guide for using direnv - a shell extension for loading directory-specific environment variables. Use when setting up project environments, creating .envrc files, configuring per-project environment variables, integrating with Python/Node/Ruby/Go layouts, working with Nix flakes, or troubleshooting environment loading issues on macOS and Linux.
Bootstrap new projects with strong typing, linting, formatting, and testing. Supports Python, TypeScript, and other languages with research fallback.
Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.
Bootstrap new projects with curated settings.local.json permissions, CLAUDE.md, and .gitignore. Detects project type (cloudflare-worker, vercel-app, node-generic, python, ops-admin) and generates grouped, commented permission presets. Also tidies existing messy settings files (removes leaked secrets, shell fragments, deprecated MCP refs, duplicate entries). Trigger with 'kickoff', 'new project', 'bootstrap', 'setup claude', 'tidy permissions', 'clean settings', or 'init project'.
Common AWS CDK patterns and constructs for building cloud infrastructure with TypeScript, Python, or Java. Use when designing reusable CDK stacks and L3 constructs.
Set up uv (Rust-based Python package manager) in CI/CD pipelines. Use when configuring GitHub Actions workflows, GitLab CI/CD, Docker builds, or matrix testing across Python versions. Includes patterns for cache optimization, frozen lockfiles, multi-stage builds, and PyPI publishing with trusted publishing. Covers GitHub Actions setup-uv action, Docker multi-stage production/development builds, and deployment patterns.
Creates and manages project artifacts (research, spikes, analysis, plans) using templated scripts. Use when asked to "create an ADR", "research topic", "spike investigation", "implementation plan", or "create analysis". Provides standardized structure, naming conventions, and helper scripts for artifact organization. Works with .claude/artifacts/ directory, Python scripts, and markdown templates.
Evidence-based test debugging enforcing systematic root cause analysis. Use when tests are failing, pytest errors occur, test suite not passing, debugging test failures, or fixing broken tests. Prevents assumption-based fixes by enforcing proper diagnostic sequence. Works with Python (.py), JavaScript/TypeScript (.js/.ts), Go, Rust test files. Supports pytest, jest, vitest, mocha, go test, cargo test, and other frameworks.
Detect Single Responsibility Principle (SRP) violations using multi-dimensional analysis. Use when reviewing code for "SRP", "single responsibility", "god class", "doing too much", "too many dependencies", before commits, during refactoring, or as quality gate. Analyzes Python, JavaScript, TypeScript files with AST-based detection, metrics (TCC, ATFD, WMC), and project-specific patterns. Provides actionable fix guidance with refactoring estimates.
Provides 3-tier validation approach for Home Assistant dashboards including pre-publish validation (entity checks, config structure), post-publish verification (log analysis), and visual validation (browser console, rendering). Use when validating HA dashboards, checking dashboard configs, verifying entity IDs, debugging rendering issues, or before deploying dashboard changes. Triggers on "validate dashboard", "check HA config", "dashboard errors", "entity not found", or "test dashboard". Works with Home Assistant WebSocket/REST APIs, Chrome extension MCP tools, Python dashboard builders, and YAML dashboard configurations.
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.