智能代理框架 是 AI Skill Hub 本期精选Cursor规则之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
智能代理框架 是一套专为 Cursor AI 代码编辑器定制的编程规范规则集。通过精心设计的规则约束,它能引导 AI 生成符合团队标准的高质量代码,减少人工审查成本,保障代码风格一致性。适合个人开发者快速提升代码质量,也适合团队统一 AI 辅助编程的规范。
智能代理框架 是一套专为 Cursor AI 代码编辑器定制的编程规范规则集。通过精心设计的规则约束,它能引导 AI 生成符合团队标准的高质量代码,减少人工审查成本,保障代码风格一致性。适合个人开发者快速提升代码质量,也适合团队统一 AI 辅助编程的规范。
# 在 Cursor 中安装规则 # 1. 打开 Cursor → Cmd+Shift+P # 2. 搜索 "Open Cursor Settings" 或直接进入 Settings # 3. 找到 "Rules for AI" / "Cursor Rules" 配置项 # 4. 粘贴本工具的规则内容 # 也可以克隆仓库后本地导入 git clone https://github.com/KbWen/agentic-os # 按照 README 中的说明添加规则文件
# 命令行使用
agentic-os --help
# 基本用法
agentic-os input_file -o output_file
# Python 代码中调用
import agentic_os
# 示例
result = agentic_os.process("input")
print(result)
# agentic-os 配置文件示例(config.yml) app: name: "agentic-os" debug: false log_level: "INFO" # 运行时指定配置文件 agentic-os --config config.yml # 或通过环境变量配置 export AGENTIC_OS_API_KEY="your-key" export AGENTIC_OS_OUTPUT_DIR="./output"
<p align="center"> <strong>A governance-first layer for AI coding agents</strong> — Claude Code, Codex, Antigravity, Cursor, Copilot.<br/> Your agent can still cut a corner; the ones that burn you — leaked secrets, missing tests, skipped gates —<br/> get caught by machine checks, not by trusting it to self-report. </p>
<p align="center"> <a href="https://github.com/KbWen/agentic-os/releases"><img src="https://img.shields.io/github/v/release/KbWen/agentic-os?style=flat-square&label=release" alt="Release"/></a> <a href="https://github.com/KbWen/agentic-os/actions/workflows/validate.yml"><img src="https://img.shields.io/github/actions/workflow/status/KbWen/agentic-os/validate.yml?branch=main&style=flat-square&label=CI" alt="CI Status"/></a> <a href="https://github.com/KbWen/agentic-os/actions/workflows/security.yml"><img src="https://img.shields.io/github/actions/workflow/status/KbWen/agentic-os/security.yml?branch=main&style=flat-square&label=Security" alt="Security Scan"/></a> <a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-22c55e?style=flat-square" alt="MIT License"/></a> </p>
<p align="center"> <a href="docs/README_zh-TW.md">繁體中文</a> · <a href="https://github.com/KbWen/agentic-os/blob/main/CONTRIBUTING.md">Contributing</a> · <a href="https://github.com/KbWen/agentic-os/blob/main/CHANGELOG.md">Changelog</a> </p>
---
Prerequisites:
| Dependency | Required? | Purpose |
|---|---|---|
| **Git** | Required | Clone and deploy the framework |
| **Bash** | Required | Run deploy & validate scripts (Git Bash from [Git for Windows](https://gitforwindows.org/) is enough on Windows) |
| **Python 3.9+** | Recommended | Enables full validation (metadata, encoding, command sync checks) |
| **SHA-256 tool** | Required for deploy | sha256sum, shasum, or openssl (pre-installed on most systems) |
No Python? The framework deploys and works without Python. Validation runs in degraded mode — Python-dependent checks reportWARNinstead ofFAIL. Pass--no-pythonto suppress warnings from a Git Bash or POSIX shell:bash .agentcortex/bin/validate.sh --no-python. On Windows PowerShell, preferpowershell -ExecutionPolicy Bypass -File .\.agentcortex\bin\validate.ps1 -NoPython.
Install (first time):
```bash
./agentic-os/installers/deploy_brain.sh --dry-run /path/to/your-project
./agentic-os/installers/deploy_brain.sh /path/to/your-project
**Update (after first install):** the installer lives inside your project. Run it from your project root — it reads the deploy manifest and auto-fetches the latest framework version from GitHub.
bash bash installers/deploy_brain.sh .
> **Existing files won't be overwritten.** If your project already has `AGENTS.md`, `CLAUDE.md`, or other framework-managed files, they are preserved. The new framework version is saved as `<filename>.acx-incoming` sidecar. Review and merge manually — or ask your AI agent: *"Merge each .acx-incoming into its target, preserving my project-specific content and adopting framework updates."*
> **AI-agent install:** If you're asking an AI assistant to install Agentic OS, point it to this README. The commands above are deterministic — no platform-specific heuristics required.
**Optional local pre-commit validation:** enable the bundled Git hook sample to run Agentic OS validation before each commit.
bash cp .githooks/pre-commit.guard-ssot.sample .githooks/pre-commit chmod +x .githooks/pre-commit git config core.hooksPath .githooks
On Windows, run the setup from PowerShell:
powershell Copy-Item .githooks\pre-commit.guard-ssot.sample .githooks\pre-commit git config core.hooksPath .githooks
The hook runs `validate.ps1` from Git Bash on Windows when PowerShell is available, otherwise it runs `validate.sh`. Validator failures block the commit; guarded SSoT receipt warnings remain advisory.
<details>
<summary><b>Windows (PowerShell / CMD)</b></summary>
powershell
powershell -ExecutionPolicy Bypass -File .\agentic-os\installers\deploy_brain.ps1 -DryRun C:\path\to\your-project
powershell -ExecutionPolicy Bypass -File .\agentic-os\installers\deploy_brain.ps1 C:\path\to\your-project
powershell -ExecutionPolicy Bypass -File .\installers\deploy_brain.ps1 .
powershell -ExecutionPolicy Bypass -File .\.agentcortex\bin\validate.ps1
powershell -ExecutionPolicy Bypass -File .\.agentcortex\bin\validate.ps1 -NoPython
Most of the framework is rules — plan before coding, don't refactor what nobody asked for, declare your confidence. An agent can ignore those, and sometimes will. The part it can't ignore is underneath:
| The failure that burns you | What catches it | When |
|---|---|---|
| A secret committed to history | scan_credentials.py (above) | pre-commit hook + CI |
| "Tests pass" with no tests | CI runs the real suite | pull request |
| A phase skipped with no evidence | validate.sh reads the work trail | pre-commit (local) |
A passing run is a receipt you can check, not a promise you take on faith.
---
.\agentic-os\installers\deploy_brain.cmd C:\path\to\your-project
Use the PowerShell entrypoint when possible. It resolves Git Bash directly and does not require a WSL distro.
Git Bash is still required on Windows for shell-based deploy and validation scripts; the PowerShell entrypoint simply locates and invokes it for you.
powershell
What is Agentic OS? Agentic OS is an open-source governance framework for AI coding agents. It gives agents like Claude Code, OpenAI Codex, Cursor, GitHub Copilot, and Google Antigravity a repeatable workflow — plan, build, review, test, ship — and enforces quality gates so they can't skip steps or call a task "done" without verifiable evidence.
How is it different from Cursor Rules or a plain AGENTS.md file? A rules file tells the agent how to behave. Agentic OS adds the workflow and the gates that hold it to that behavior: phase sequencing, evidence requirements, scope discipline, and a single source of truth that remembers decisions across sessions. It's the difference between a prompt the agent might follow and a workflow it has to.
Which AI coding agents does it support? Any agent that can read Markdown instructions. It ships native entry points for Claude Code (CLAUDE.md) and Codex / Antigravity (AGENTS.md), and works with Cursor, GitHub Copilot, and other LLM agents through the same model-agnostic workflow files.
Do I need to know a specific programming language? No. The governance layer is plain Markdown. Python is optional — it only unlocks the deeper validation checks. Everything deploys and runs without it.
Does it lock me into one AI vendor? No. The workflows are model-agnostic Markdown, so the same governance works whether you switch between Claude, Codex, Gemini, or anything else.
Is it free? Yes — MIT licensed. Use it, fork it, ship it.
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高质量的AI编码代理框架,具有自动化和可扩展性
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,智能代理框架 在Cursor规则赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | agentic-os |
| Topics | agent-frameworkai-agentpython |
| GitHub | https://github.com/KbWen/agentic-os |
| License | MIT |
| 语言 | Python |
收录时间:2026-06-19 · 更新时间:2026-06-19 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端