136 boosters for "edge" — open source, verified from GitHub, ready to install
Effect Patterns Hub is an MCP server providing a community-driven knowledge base for Effect-TS design patterns and functional programming practices. It benefits TypeScript developers using Effect-TS who need structured guidance on implementing complex patterns.
Validate behavior against intent. Look for null/edge cases (0, -1, int.MaxValue, empty collections), error paths, exception handling, thread safety. Check for performance traps (allocations in hot paths, O(n²) where O(n) is possible), resource leaks (IDisposable not disposed), missing null checks on
"name": "atlas-mcp-server", "version": "2.8.15", "description": "ATLAS (Adaptive Task & Logic Automation System): An MCP server enabling LLM agents to manage projects, tasks, and knowledge via a Neo4j-backed, three-tier architecture. Facilitates complex workflow automation and project management thr
A unified skill for four interaction modes with a curated knowledge base (726 concept cards + 1282 case cards) distilled from 300+ ICT/SMC/ChanLun(缠论) trading videos and live lessons across 12 curated source collections. Any user message that mentions an asset + timeframe — even without the word "现在
Pulse Radar uses LLM pipeline to transform raw Telegram messages into structured knowledge. Core philosophy: Messages individually are noise; batched extraction reveals patterns. 1. JSON-only output — explicitly state "respond with ONLY JSON"
This MCP server enables developers to deploy HTML content directly to EdgeOne Pages and retrieve publicly accessible URLs programmatically. It's ideal for AI assistants and developers who need to quickly publish web content through Claude or automated workflows.
This booster provides expert guidance for developing, debugging, and optimizing Azure AI Document Intelligence applications, covering architecture, security, best practices, and deployment patterns. Developers building document processing solutions on Azure will benefit from its comprehensive troubleshooting and design pattern knowledge.
Procedural memory for AI coding agents. Transforms scattered sessions into persistent, cross-agent memory. Uses a three-layer cognitive architecture that mirrors human expertise development. AI coding agents accumulate valuable knowledge but it's: You've solved auth bugs three times this month acros
"description": "A virtual design team for Claude Code, Cursor, Windsurf, Gemini CLI, and Copilot — powered by Naksha. Assembles specialist roles — UI designer, UX researcher, content designer, Figma expert, data viz, email, social, motion, presentation, brand strategy, illustration, video, conversat
This repository root file is a lightweight pointer. The executable skill lives in . Load only when needed: Full website (Gallery, PBL, knowledge map, APIs) lives in the courseware repository:
"name": "comfyui-custom-node-skills", "description": "Skills for building ComfyUI custom nodes with the V3 and V1 Python APIs" "name": "comfyui-custom-nodes",
"version": "0.46.0", "description": "Build and deploy web apps and agents", "url": "https://github.com/vercel"
Skyll enables agents to dynamically discover and retrieve skills at runtime. Instead of having all skills pre-loaded, agents can search for relevant skills on-demand and inject them into context. Get a specific skill: The API returns ranked skills with relevance scores (0-100):
首次激活时，必须说一次免责声明：「我以Naval视角和你聊，基于公开言论推断，非本人观点」。此后对话绝不重复——重复 = 破坏沉浸感 = 失败。 用户说「退出 / 切回正常 / 跳出角色 / 不用扮演了 / 别演了」中任一关键词 → 立即恢复正常助手语气，不再用「我」自称 Naval，不再用 Oracle 模式短句格言，回到标准助手语气。 1. 这个机会用的是哪种杠杆：劳动/资本/代码/媒体？（搜索商业模式、产品形态）
Activate when the user says any of: If the user provides a name as an argument (e.g. ), skip Q1 in intake and use it directly as the slug. Enter evolution mode when:
This project is an MCP server that's built using Node.js and the TypeScript SDK for MCP. When working on this project, make sure to refer to the type definitions for the MCP TypeScript SDK: https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/refs/heads/main/src/types.ts.
Windsurf Rules for GuidedGenerations-Extension
Query Google's AI Search mode to retrieve comprehensive, source-grounded answers from across the web. Trigger this skill when the user: 1. Include Current Year (2026) for up-to-date results
Refero gives agents taste and product evidence. Use it before design work instead of relying on generic model knowledge. Refero has three research layers:
A fully autonomous AI research agent that ingests sources into Google NotebookLM, runs deep web research, synthesizes knowledge through cited Q&A and 9 downloadable artifact types, creates polished content drafts, and optionally publishes to social platforms.
Automatically extracts knowledge from Amp threads and synchronizes project documentation, keeping AGENTS.md and other docs up-to-date after epics and major work. Ideal for teams that need to maintain living documentation without manual overhead.
This command queries the BEADS knowledge base for facts relevant to your current context and injects them into the conversation, ensuring you: 1. Follow established patterns and rules 2. Avoid known gotchas and pitfalls
"name": "llm-wiki-compiler", "name": "llm-wiki-compiler", "source": "./plugin",
"name": "compound-knowledge-plugin", "url": "https://every.to" "description": "Workflows for knowledge work that compounds over time",
