Agent Skills Hub

cc-skill-project-guidelines-example

A template skill for creating project-specific AI agent guidelines, defining architecture, file structures, and code patterns for deterministic development.

plan-down

Method-driven planning workflow that intelligently decomposes tasks into structured plan.md files using zen-mcp tools, adapting to user clarity and automation needs.

analyze-project

Analyze project codebases to generate architecture documentation, coding standards, and development practices for AI onboarding.

components-build

Build modern, composable, and accessible React UI components following the components.build specification. Use for design systems, component libraries, and reusable UI architectures.

context-engineering-expert

Advanced context engineering system for orchestrating AI agents, memory management, and token optimization to improve long-term persistence and project intelligence.

project-development

A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.

mcp-server

Guide for integrating and managing custom Model Context Protocol (MCP) servers within the Cursor IDE environment.

creating-agents-md

Provides a standardized template and guidelines for creating agents.md files to deliver project-specific context to AI coding assistants.

shift-left-testing

Accelerate software delivery by shifting testing to the earliest development phases, using AI-driven requirements validation, TDD, and automated CI pipelines to reduce defect costs.

taskyou

An autonomous AI-powered task management system with Kanban boards, git worktree isolation, and pluggable executors like Claude Code, Gemini, and OpenAI Codex.

oracle

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

langchain-architecture

Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.