Agent Skills Hub

skill-authoring-workflow

A standardized workflow for converting raw PM notes, workshops, or rough drafts into polished, validated, and repository-compliant AI skills.

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.

image-generation

Generate high-quality visual content, characters, and scenes using structured JSON prompts and automated Python execution for guided image synthesis.

langgraph-workflows

Master multi-agent orchestration with LangGraph. Build stateful, fault-tolerant AI workflows using supervisor-worker patterns, conditional routing, and advanced state management.

prompt-injection-test

A testing utility designed to simulate prompt injection attacks and validate security scanners for AI agent skills.

oracle

CLI tool to bundle repository context, files, and prompts into a one-shot request for advanced AI debugging, refactoring, and code review.

open-source-maintainer

End-to-end GitHub repository maintenance agent. Automates triage, PR review, issue analysis, and maintenance reporting to ensure long-term repository health, stability, and growth.

artifact-tracking

AI-optimized artifact tracking system for token-efficient project orchestration, phase management, and automated task delegation using YAML-Markdown hybrid formats.

ctx-upgrade

Update context-mode to the latest version, rebuild assets, reinstall global NPM dependencies, and refresh hook configurations.

gemini-interactions-api

Expert skill for implementing the Gemini Interactions API. Use for stateful multi-turn chat, background Deep Research agent tasks, function calling, structured outputs, and modern Python/TypeScript SDK integration.

upstash-vector-db-skills

Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.

claude-starter

An AI-powered skill that automatically retrieves relevant project context from your RAG knowledge base for complex coding tasks.