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Story brainstorming capture — minimal notes that preserve creative freedom. Use when exploring narrative ideas, discussing characters, planning chapters, or thinking through story possibilities. Supports interactive conversation and autonomous report mode for fan-out exploration.
Faz análise de postura de testes (presença, estrutura, camadas).
Develop Dominion addon plugins using the DominionAPI. Use when creating new Dominion addon plugins, writing code that interacts with the Dominion land-claim system, listening to Dominion events, operating on dominion/group/member data via Providers, registering custom flags, or checking privilege/environment flags within dominions. Also use when setting up Gradle/Maven build files for DominionAPI dependency, creating plugin.yml for Dominion addons, or debugging Dominion API integration issues.
Fetches official documentation for external libraries and frameworks (React, Next.js, Prisma, FastAPI, Express, Tailwind, MongoDB, etc.) with 60-90% token savings via content-type filtering. Use this skill when implementing features using library APIs, debugging library-specific errors, troubleshooting configuration issues, installing or setting up frameworks, integrating third-party packages, upgrading between library versions, or looking up correct API patterns and best practices. Triggers automatically during coding work - fetch docs before writing library code to get correct patterns, not after guessing wrong.
This skill should be used when evaluating UI components against UX best practices. Use for reviewing buttons, navigation elements, spacing, visual hierarchy, or any interface element. Provides a systematic 3-dimension framework (Position, Visual Weight, Spacing) aligned with industry standards (Balsamiq, Nielsen heuristics). Invoke when user asks to "review UX", "check button design", "evaluate layout", or references design guidelines.
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。
增长模型分析技能 - 提供全面的增长黑客分析工具，包括裂变策略评估、用户细分、Uplift建模、ROI优化等。支持多种增长场景的机器学习建模和智能决策建议。适用于用户增长、营销优化、产品迭代等增长分析场景。
Optimizes content for Generative Engine Optimization (GEO) to increase chances of being cited by AI systems like ChatGPT, Claude, Perplexity, and Google AI Overviews. Makes content AI-friendly while maintaining SEO value.
POST-GATE TOOL. Refine verbose content by eliminating redundancy, trimming word count, and strengthening lesson connections. Use ONLY to fix Gate 4 failures.
Analyzes competitor SEO and GEO strategies including their ranking keywords, content approaches, backlink profiles, and AI citation patterns. Reveals opportunities to outperform competition.
Analyzes search engine results pages (SERPs) to understand ranking factors, SERP features, user intent patterns, and AI overview triggers. Essential for understanding what it takes to rank.
Creates production-grade, reusable skills that extend Claude's capabilities. This skill should be used when users want to create a new skill, improve an existing skill, or build domain-specific intelligence. Gathers context from codebase, conversation, and authentic sources before creating adaptable skills.
Build AI chat interfaces with custom backends, authentication, and context injection. Use when integrating chat UI with AI agents, adding auth, or injecting user/page context. Covers ChatKitServer, useChatKit, and MCP auth patterns.
Design reusable prompt templates that encode domain-specific patterns for recurring AI tasks. Use when you've executed similar prompts 2+ times and need to capture the pattern as reusable intelligence. NOT for one-off prompts or generic "ask AI a question" patterns.
Use when building AI agents with Anthropic's Claude Agent SDK (formerly Claude Code SDK). Triggers include creating autonomous agents, building agentic applications, SDK-based automation, implementing hooks/subagents/MCP servers, session management, or agent tool usage. NOT when using Claude API directly (use anthropic-sdk) or building MCP servers from scratch (use mcp-builder).
Build production RAG systems with LangChain orchestration and Qdrant vector store. Covers 8 RAG architectures (Simple, HyDE, CRAG, Self-RAG, Agentic), document processing, semantic chunking, retrieval chains, and evaluation with LangSmith/RAGAS. Use when implementing RAG pipelines, semantic search, or AI knowledge systems. NOT for simple keyword search.
Apply optimization techniques to extend effective context capacity. Use when context limits constrain agent performance, when optimizing for cost or latency, or when implementing long-running agent systems.
Use when building AI agents with OpenAI's Agents SDK. Triggers include creating agents, implementing tools, multi-agent handoffs, guardrails, MCP integration, tracing. Also for using LiteLLM to run agents on free/alternative models (Anthropic, Gemini). NOT for general OpenAI API usage (use openai-python SDK docs instead).
Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.
