204 boosters for "coding" — open source, verified from GitHub, ready to install
Heuristic scoring (no AI key configured).
"name": "cc-skills-golang", "description": "AI Agent Skills for production-ready Go projects", "name": "Samuel Berthe",
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"name": "pro-workflow", "description": "Complete AI coding workflow system. Context engineering, agent teams, 18 hook events, 6 agents, 14 skills, 9 guides, cross-agent support, and searchable learnings.", "name": "Rohit Ghumare",
"name": "safety-net", "description": "Block destructive git and filesystem commands before execution", "email": "jliew@420024lab.com"
Agor Live is a multiplayer canvas MCP server that enables collaborative AI coding sessions, allowing developers to orchestrate and synchronize Claude-based coding workflows across team members in real-time.
Use this skill to configure FreeTheAi for a user or another AI agent. FreeTheAi is an OpenAI-compatible gateway with one key, one base URL, and multiple public model aliases. 1. Send the user to . 2. Tell them to run in Discord and complete the modal.
Use this skill when the user wants a repeatable, auditable implementation workflow for a non-trivial coding task, especially a feature, refactor, migration, or bug fix that should leave repo-local proof in . All task artifacts created by this workflow must stay inside the repository. When the exampl
"name": "spec-driven-develop", "name": "zhu1090093659" "description": "Automates pre-development workflow for large-scale complex tasks"
A Cursor-integrated coding standard guide for the Dingo SDK that enforces PEP 8 conventions, type hints, and proper lazy-import patterns for optional dependencies. Developers building with or contributing to Dingo benefit from consistent, maintainable Python code patterns.
Comprehensive guide for Claude Code CLI tool, extensibility (agents/skills/output styles), and CLAUDE.md architecture. 1. Task verbs: create, build, debug, fix, deploy 2. Problem descriptions: slow, broken, failing
1. Write Simple, Clear Code 3. Project Structure 4. Development Practice
"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",
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.
VTCode is a system prompt designed to enhance a semantic AI coding agent for terminal-based development environments, providing clearer instructions and error handling for developers using Claude, Cursor, Windsurf, or ChatGPT.
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
<example type="invalid"> npm install --save-dev eslint npm uninstall lodash
A system prompt for training AI agents on terminal/coding tasks using GRPO, enabling autonomous task completion in containerized Linux environments. Ideal for developers building advanced AI coding assistants and automation systems.
"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"
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.
1. Maintainability over Speed: Prioritize long-term code health over initial development velocity 2. Simplicity First: Choose the simplest solution that meets requirements (YAGNI principle) 3. Explicit over Implicit: Make intentions clear through code structure and naming
"name": "claude-buddy", "description": "Permanent coding companion for Claude Code \u2014 survives any update. MCP-based terminal pet with ASCII art, stats, reactions, and personality.", "repository": "https://github.com/1270011/claude-buddy",
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
