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Found 1,319 Skills
Build AdonisJS 6 features from scratch through production. Full lifecycle - build, debug, test, optimize, refactor. Follows TypeScript-first, Lucid ORM, and AdonisJS conventions.
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
Ultracite is a zero-config linting and formatting preset for JavaScript/TypeScript projects. Use when: (1) Setting up or initializing Ultracite in a project (ultracite init), (2) Running linting or formatting commands (check, fix, doctor), (3) Writing or reviewing JS/TS code in a project that uses Ultracite — to follow its code standards, (4) Troubleshooting linting/formatting issues, (5) User mentions 'ultracite', 'lint', 'format', 'code quality', or 'biome/eslint/oxlint' in a project with Ultracite installed.
Setup Sentry Metrics in any project. Use this when asked to add Sentry metrics, track custom metrics, setup counters/gauges/distributions, or instrument application performance metrics. Supports JavaScript, TypeScript, Python, React, Next.js, and Node.js.
Setup Spanora AI observability in any project (JavaScript/TypeScript or Python). Use when user asks to "add spanora", "setup spanora", "integrate spanora", "add AI observability", "monitor LLM calls with spanora", "track AI costs", or mentions spanora in the context of adding observability to their project. Detects the language and installed AI SDKs (Vercel AI, Anthropic, OpenAI, LangChain) and configures the optimal integration pattern.
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.
Common AWS CDK patterns and constructs for building cloud infrastructure with TypeScript, Python, or Java. Use when designing reusable CDK stacks and L3 constructs.
Finds all REFACTOR markers in codebase, validates associated ADRs exist, identifies stale markers (30+ days old), and detects orphaned markers (no ADR reference). Use during status checks, before feature completion, or for refactor health audits. Triggers on "check refactor status", "marker health", "what's the status", or PROACTIVELY before marking features complete. Works with Python (.py), TypeScript (.ts), and JavaScript (.js) files using grep patterns to locate markers and validate against ADR files in docs/adr/ directories.
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.
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.