Catalog
Every x402, MPP, MCP, and skill listing we've indexed, normalized, and enriched.
verify
AI DevKit · Enforce evidence-based completion claims — require fresh command output before reporting success. Use when completing any task, fixing a bug, finishing a phase, running tests, building, deploying, or making any "it works" claim.
technical-writer
AI DevKit · Review and improve documentation for novice users. Use when users ask to review docs, improve documentation, audit README files, evaluate API docs, review guides, or improve technical writing.
tdd
AI DevKit · Test-driven development — write a failing test before writing production code. Use when implementing new functionality, adding behavior, or fixing bugs during active development.
simplify-implementation
AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical
memory
AI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.
dev-lifecycle
AI DevKit · Structured SDLC workflow with 8 phases — requirements, design review, planning, implementation, testing, and code review. Use when the user wants to build a feature end-to-end, or run any individual phase (new requirement, review requirements, review design, execute p
debug
AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose
capture-knowledge
AI DevKit · Capture structured knowledge about a code entry point and save it to the knowledge docs. Use when users ask to document, understand, or map code for a module, file, folder, function, or API.
agent-orchestration
AI DevKit · Proactively orchestrate running AI agents — scan statuses, assess progress, send next instructions, and coordinate multi-agent workflows. Use when users ask to manage agents, orchestrate work across agents, or check on agent progress.
golang-testing
Provides a comprehensive guide for writing production-ready Golang tests. Covers table-driven tests, test suites with testify, mocks, unit tests, integration tests, benchmarks, code coverage, parallel tests, fuzzing, fixtures, goroutine leak detection with goleak, snapshot testin
golang-lint
Provides linting best practices and golangci-lint configuration for Go projects. Covers running linters, configuring .golangci.yml, suppressing warnings with nolint directives, interpreting lint output, and managing linter settings. Use this skill whenever the user runs linters,
web-design-guidelines
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", "check my site against best practices", or "web interface guidelines".
vercel-react-best-practices
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching,
security-patterns
Implements authentication, authorization, encryption, secrets management, and security hardening patterns. Use when designing auth flows, managing secrets, configuring CORS, implementing rate limiting, or when asked about JWT, OAuth, password hashing, API keys, RBAC, or security
parallel-execution
Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.
optimizing-performance
Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.
managing-git
Manages Git workflows including branching, commits, and pull requests. Use when working with Git, creating commits, opening PRs, managing branches, resolving conflicts, or when asked about version control best practices.
error-handling
Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alertin
devops-infrastructure
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infra
designing-tests
Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.
designing-architecture
Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.
designing-apis
Designs REST and GraphQL APIs including endpoints, error handling, versioning, and documentation. Use when creating new APIs, designing endpoints, reviewing API contracts, or when asked about REST, GraphQL, or API patterns.
database-design
Designs database schemas, indexing strategies, query optimization, and migration patterns for SQL and NoSQL databases. Use when designing tables, optimizing queries, fixing N+1 problems, planning migrations, or when asked about database performance, normalization, ORMs, or data m
convex-backend
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.