490 boosters for "agents" — open source, verified from GitHub, ready to install
This skill provides production-ready operational patterns for designing, building, evaluating, and deploying AI agents. It centralizes procedures, checklists, decision rules, and templates used across RAG agents, tool-using agents, OS agents, and multi-agent systems. No theory. No narrative. Only wh
A comprehensive, structured workflow for feature development with specialized agents for codebase exploration, architecture design, and quality review. Launch the guided feature development workflow: The workflow will guide you through 7 distinct phases automatically.
Consult ChatGPT for a second opinion on debugging, architecture, or best practices questions. This skill implements caching to avoid redundant calls. The arguments should contain your consultation context. Structure it roughly as:
"name": "langchain-skills", "description": "Agent skills for building agents with LangChain, LangGraph, and Deep Agents", "name": "LangChain",
"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
1. Write Simple, Clear Code 3. Project Structure 4. Development Practice
Sub-Agents is a lightweight framework for decomposing complex tasks into specialized child agents that collaborate under a parent orchestrator agent. Developers building multi-agent systems in Python will benefit from this pattern for creating modular, reusable agent hierarchies.
"description": "Canary browser automation + recorded QA sessions: a sandbox scripting reference, verify/automate/session/review skills, JTBD subagents, and /canary slash commands.", "name": "wizenheimer", "url": "https://github.com/wizenheimer"
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"
"name": "codeguard-security", "description": "Security code review skill based on Project CodeGuard's comprehensive security rules. Helps AI coding agents write secure code and prevent common vulnerabilities.", "name": "Project CodeGuard",
"name": "ensue-memory", "description": "Persistent memory layer for AI agents via Ensue Memory Network", "email": "founders@ensue.dev"
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
Accessible workspace directory: !!<<<<||||workspace_dir||||>>>>!! When processing tasks, if you need to read/write local files and the user provides a relative path, you may choose to combine it with the above workspace directory to get the complete path. If you believe the task is completed, you ca
"name": "power-bi-agentic-development", "version": "0.19.0", "description": "A marketplace for skills and tools for agentic Power BI development.",
Graphlit MCP Server integrates the Graphlit knowledge graph platform with Claude, enabling developers to build AI agents with RAG capabilities, document parsing, and intelligent retrieval. It's ideal for teams building document-heavy AI applications, knowledge management systems, and enterprise AI agents.
Read AGENTS.md and rules/. Milady's Electrobun workspace is eliza/packages/app-core/platforms/electrobun; renderer app is apps/app. Electrobun/Bun/TypeScript only. Inspect before edit. Prefer typed RPC, sandboxed webviews, Bun tests, Bun.secrets, bun:sqlite, Electrobun updater/signing automation. Do
"description": "Open-source cross-agent memory layer for coding agents across Cursor, Claude Code, Codex, Windsurf, Gemini CLI, Copilot, Kiro, OpenCode, Antigravity, and Trae via MCP.", "sideEffects": false, "memorix": "./dist/cli/index.js"
LC-StudyLab provides Cursor IDE rules and documentation links for LangChain v1.0, enabling developers to quickly reference core components and advanced features while coding with LangChain's full ecosystem.
AgentRecall is a persistent memory system. Default surface: 5 tools (two verbs + three essentials). Full surface: 18 tools via . This guide describes how and when to use them. AgentRecall requires the MCP server to be running. If tool calls fail with "unknown tool", the human needs to install it fir
A PHP SDK for building AI agents with structured outputs and multi-agent orchestration, enabling developers to decompose complex tasks into specialized subagents with isolated contexts and independent execution.
A Python SDK for building production-ready agentic AI applications with Claude, featuring agents, handoffs, and guardrails for complex multi-agent workflows. Developers building AI agents and multi-tool systems will benefit from this lightweight, easy-to-learn framework.
Analyze various aspects of aired TV series, including series information retrieval, scene-by-scene analysis, story five elements analysis, web search, and result integration. 1. Series Information Retrieval: Obtain series basic information (such as director, actors, ratings, episode plots, etc.). 2.
"version": "2.0.12", "description": "Social media automation CLI for scheduling posts, managing integrations, uploading media, and tracking analytics across 28+ platforms including X, LinkedIn, Reddit, YouTube, TikTok, Instagram, and more", "name": "Nevo David",
You solve problems by decomposing them: break big tasks into smaller ones, delegate to sub‑agents, combine results. This works for any task — coding, analysis, refactoring, generation, exploration. Your original prompt is also available as a file at — use it when you need to manipulate the question
