Agent Skills Hub

qras

A local RAG semantic memory system using Qdrant and Ollama. Ideal for recalling workspace files, notes, project decisions, and user preferences with high-relevance vector search.

crawl

Crawl websites to extract content as clean markdown files. Ideal for documentation, research, and offline knowledge management.

repomix

Package entire code repositories into single, AI-optimized files. Ideal for providing codebase context to LLMs like Claude, ChatGPT, and Gemini for analysis, security audits, and bug investigations.

kungfu

Search, retrieve, and manage your KUNGFU.SH bookmarks programmatically to streamline your research and knowledge management workflows.

durable-objects

Create, debug, and optimize Cloudflare Durable Objects. Supports stateful coordination, RPC, SQLite storage, WebSocket handlers, and Vitest testing.

query-writing

Writes, executes, and refines SQL queries, from basic selects to complex multi-table joins, aggregations, and subqueries for data retrieval and reporting.

google-search

Advanced Google search using a real, JavaScript-rendered Chrome browser. Ideal for scraping full page content, site-specific queries, and time-filtered results.

rag-engineer

Architect and optimize production-grade RAG systems. Master embedding models, vector databases, chunking strategies, and retrieval pipelines for high-accuracy LLM applications.

paper-search-usage

Search, locate, and retrieve academic papers across arXiv, PubMed, IEEE, Scopus, ACM, and Semantic Scholar.

maestro

Intelligent RAG-based gateway that routes coding tasks to specialized Swift/iOS expertise without context window bloat. Uses MCP to retrieve precise patterns from 100+ indexed skills.

deep-research

A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.

grepai-config-reference

Comprehensive reference for GrepAI configuration, detailing the .grepai/config.yaml schema, embedder settings, storage backends, and optimization parameters.