JeremyDev87JeremyDev87/codingbuddy/AGENTS.md

codingbuddy

AGENTS.md31 starsChanged 7 months agoMITView on GitHub

This project uses codingbuddy MCP server to manage AI Agents. → parse_mode tool is automatically called, loading appropriate Agent and rules. Direct file references work within this repository: Multi-language keywords supported: - 한국어: 계획, 실행, 평가 - 日本語: 計画, 実行, 評価 - 中文: 计划, 执行, 评估 - Español: PLANIFICAR, ACTUAR, EVALUAR

In this repository9 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/auto-agent.mdcCursor rule
- .cursor/rules/imports.mdcCursor rule
- parallel-issuesSkill
- plan-to-issuesSkill
- retroSkill
- shipSkill
- taskmaestroSkill

The file

Create a free account to mount

Files

AGENTS.md

This project uses codingbuddy MCP server to manage AI Agents.

Quick Start

For End Users (Your Project)

Install MCP Server

// Claude Code: .claude/settings.json
{
  "mcpServers": {
    "codingbuddy": {
      "command": "npx",
      "args": ["-y", "codingbuddy"]
    }
  }
}

// Cursor: .cursor/mcp.json
{
  "mcpServers": {
    "codingbuddy": {
      "command": "npx",
      "args": ["-y", "codingbuddy"]
    }
  }
}

Use Mode Keywords
```
PLAN Design a login feature
```
→ parse_mode tool is automatically called, loading appropriate Agent and rules.

For Monorepo Contributors

Direct file references work within this repository:

Workflow: packages/rules/.ai-rules/rules/core.md
Coding principles: packages/rules/.ai-rules/rules/augmented-coding.md
Agent list: packages/rules/.ai-rules/agents/README.md

Workflow Modes

Keyword	Mode	Description
`PLAN`	Plan	Design and planning before implementation
`ACT`	Act	Implement code following the plan
`EVAL`	Eval	Code quality review and improvement

Multi-language keywords supported:

한국어: 계획, 실행, 평가
日本語: 計画, 実行, 評価
中文: 计划, 执行, 评估
Español: PLANIFICAR, ACTUAR, EVALUAR

MCP Tools

Tool	Purpose
`parse_mode`	Parse mode keywords, load Agent and rules
`get_agent_details`	Get specific Agent details
`get_project_config`	Get project configuration
`recommend_skills`	Recommend skills based on prompt
`search_rules`	Search across all rules

Reference

Rules: packages/rules/.ai-rules/rules/
Agents: packages/rules/.ai-rules/agents/
Skills: packages/rules/.ai-rules/skills/
MCP API: docs/api.md

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

It worked
Partly
It didn't

What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free