Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

Fully autonomous TDD with strict guardrails. Use when you want the AI to drive the entire RED-GREEN-REFACTOR cycle independently while maintaining TDD discipline.

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This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM...

This skill should be used ONLY when the user asks to update README.md, CLAUDE.md, AGENTS.md, or CONTRIBUTING.md. Trigger phrases include "update README", "update context files", "init context",...

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Initialize a PRD (Product Requirements Document) for structured ralph-loop execution

LLM application architecture expert for RAG, prompting, agents, and production AI systemsUse when "rag system, prompt engineering, llm application, ai agent, structured output, chain of thought,...

选题系统主控Agent。协调热点采集、选题生成、选题审核三个环节，支持迭代直到产出合格选题。触发方式：(1)"开始今日选题"启动完整流程 (2)"今日AI热点"只采集热点不生成选题 (3)"我有一个选题"进入单个选题分析 (4)"推荐一些好的选题"直接输出推荐。输出保存到Obsidian选题库。

This skill provides a complete SEO content workflow for creating, analyzing, and optimizing long-form blog content. Use when the user wants to research topics, write SEO-optimized articles,...

Use when user wants to create a new Next.js 15 project (Todo/Blog/Dashboard/E-commerce/Custom domain) with App Router, ShadCN, Zustand, Tanstack Query, and modern Next.js stack

Complete shadcn/ui component library guide including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building...

This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural...

Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG,...

This skill should be used when the user asks to "start an LLM project", "design batch pipeline", "evaluate task-model fit", "structure agent project", or mentions pipeline architecture,...

This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions...