NLP

Constroi servidores MCP (Model Context Protocol) para conectar o Claude ao banco de dados PostgreSQL e APIs do PCA Camocim.

Use fresh agents for focused subtasks to avoid context pollution

Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.

WHEN: Context setup, token optimization, MCP/agent configuration requests WHAT: Project analysis + Preset recommendation + MCP server selection + Agent activation + Config generation WHEN NOT: Status check only → /context-status command

Track complex, multi-session work with dependency graphs using beads (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.

LLM이 잘 설계된 도구를 통해 외부 서비스와 상호작용할 수 있게 해주는 고품질 MCP (Model Context Protocol) 서버를 만들기 위한 가이드입니다. Python (FastMCP) 또는 Node/TypeScript (MCP SDK)를 사용하여 외부 API나 서비스를 통합하는 MCP 서버를 구축할 때 사용하세요.

Enterprise Supabase PostgreSQL Platform with AI-powered open-source BaaS architecture, Context7 integration, and intelligent PostgreSQL orchestration for scalable modern applications

ADHD-optimized task state machine with abandonment detection and interventions. Use when: (1) user initiates any task, (2) providing solutions to problems, (3) detecting context switches, (4) user says "done", "completed", "finished", (5) session ends with pending tasks, (6) >30 minutes since solution provided. Tracks complexity, clarity, domain (BUSINESS/MICHAEL/FAMILY/PERSONAL), and triggers interventions.

Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.

Provides context about Ed, his mission, terminology, and business. Use when working on Ed's projects, coaching business, AI Powerhouse content, BlackBelt work, or The Little Blue Report. Also use when Ed asks you to understand his business or speak in his voice.

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context

Image generation with Google's Imagen and Gemini native models. Text-to-image, image editing, and iterative refinement.

Guide for creating and maintaining repository-local CLAUDE.md files that capture project-specific context, patterns, and conventions. Use when initializing repositories for Claude Code, updating project memory, or understanding effective repository memory structure.

Generate conventional commit messages from staged changes by inspecting diffs, picking the correct type/scope, and writing the final text to the prompt-specified file.

Analyze project briefs to resolve architectural ambiguity before tech stack selection. Determines greenfield vs brownfield, platform constraints, integration requirements, scale expectations, and team context. Produces architecture-context.json for downstream skills.

Context isolation for query-type MCP tools (LSP, search, database) via external CLI. Use when MCP query results consume too many context tokens.

Use this skill when you need to start or call Chitti's MCP server (chitti.decide/recall/policy/audit) from Codex, keeping tool details out of context until invoked.

Official skill for @foxruv/iris. Handles installation, configuration, optimization (Ax/DSPy), multi-agent context generation, and natural language reporting.

Enriches Jira tasks with comprehensive context, requirements analysis, and technical details through intelligent extraction, dependency mapping, and historical analysis