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Found 5,632 Skills
Configure Qdrant vector database for GrepAI. Use this skill for high-performance vector search.
Transform legacy codebases into AI-ready projects with Claude Code configurations. Use when (1) analyzing old projects to generate AI coding configurations, (2) creating CLAUDE.md, skills, subagents, slash commands, hooks, or rules for existing projects, (3) user wants to enable vibe coding for a codebase, (4) onboarding new team members with AI-assisted development, (5) user mentions "make project AI-ready", "generate Claude config", or "create coding standards for AI".
Build a complete AI chat application with database persistence, chat list management, and automatic title generation.
Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.
Guides and best practices for working with Neon Serverless Postgres. Covers getting started, local development with Neon, choosing a connection method, Neon features, authentication (@neondatabase/auth), PostgREST-style data API (@neondatabase/neon-js), Neon CLI, and Neon's Platform API/SDKs. Use for any Neon-related questions.
Find unused functions and dead code in the codebase
Generate hierarchical AGENTS.md structures for codebases. Use when user asks to create AGENTS.md files, analyze codebase for AI agent documentation, set up AI-friendly project documentation, or generate context files for AI coding assistants. Triggers on "create AGENTS.md", "generate agents", "analyze codebase for AI", "AI documentation setup", "hierarchical agents".
Deep codebase initialization with hierarchical AGENTS.md documentation
This skill should be used for structured feature development with codebase understanding. Triggers on /do command. Provides a 5-phase workflow (Understand, Clarify, Design, Implement, Complete) using codeagent-wrapper to orchestrate code-explorer, code-architect, code-reviewer, and develop agents in parallel.
Performance optimization specialist for profiling, caching, and latency optimizationUse when "performance, latency, slow query, profiling, caching, optimization, N+1, connection pool, p99, performance, profiling, caching, latency, optimization, async, database, load-testing, ml-memory" mentioned.
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when "building RAG, vector search, embeddings, semantic search, document retrieval, context retrieval, knowledge base, LLM with documents, chunking strategy, pinecone, weaviate, chromadb, pgvector, rag, embeddings, vector-database, retrieval, semantic-search, llm, ai, langchain, llamaindex" mentioned.
Generates deterministic seed data for development and testing with factory functions, realistic fixtures, and database reset scripts. Use for "data seeding", "test fixtures", "database seeding", or "mock data generation".