AI代码守护 是 AI Skill Hub 本期精选Agent工作流之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
AI代码守护 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
AI代码守护 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install agentlint
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install agentlint
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/mauhpr/agentlint
cd agentlint
pip install -e .
# 验证安装
python -c "import agentlint; print('安装成功')"
# 命令行使用
agentlint --help
# 基本用法
agentlint input_file -o output_file
# Python 代码中调用
import agentlint
# 示例
result = agentlint.process("input")
print(result)
# agentlint 配置文件示例(config.yml) app: name: "agentlint" debug: false log_level: "INFO" # 运行时指定配置文件 agentlint --config config.yml # 或通过环境变量配置 export AGENTLINT_API_KEY="your-key" export AGENTLINT_OUTPUT_DIR="./output"
Real-time guardrails for AI coding agents — code quality, security, and infrastructure safety.
Works with Claude Code, Cursor, Kimi, Grok, Gemini, Codex, Continue.dev, OpenAI Agents SDK, MCP hosts, and custom frameworks.
AI coding agents drift during long sessions — they introduce API keys into source, skip tests, force-push to main, and leave debug statements behind. AgentLint catches these problems as they happen, not at review time.
Architecture overview: docs/architecture.md
| Platform | Setup command | Integration style |
|---|---|---|
| Claude Code | agentlint setup claude | Native hooks in .claude/settings.json or user settings |
| Cursor IDE | agentlint setup cursor | Native hooks in .cursor/hooks.json |
| Codex CLI | agentlint setup codex | Native hooks in .codex/hooks.json; Bash coverage is strongest |
| Gemini CLI | agentlint setup gemini | Native hooks in .gemini/settings.json |
| Continue.dev | agentlint setup continue | Native hooks in .continue/settings.json |
| Kimi Code CLI | agentlint setup kimi | Native TOML hooks |
| Grok CLI | agentlint setup grok | Native JSON hooks |
| OpenAI Agents SDK | agentlint setup openai | Guardrail integration code |
| MCP hosts | agentlint setup mcp | MCP server config |
| Custom tools | agentlint setup generic | Generic normalized HTTP/webhook adapter |
For platform-specific details, use the setup guides in docs/:
Pick the AI coding agent you actually use:
pip install agentlint
cd your-project
agentlint setup claude # Claude Code
agentlint setup cursor # Cursor
agentlint setup codex # Codex CLI
agentlint setup gemini # Gemini CLI
Run agentlint setup --help for the full platform list. agentlint setup resolves the absolute path to the binary, so hooks work regardless of your shell's PATH — whether you installed via pip, pipx, uv, poetry, or a virtual environment.
When AgentLint blocks a dangerous action, the agent sees:
⛔ [no-secrets] Possible secret token detected (prefix 'sk_live_')
💡 Use environment variables instead of hard-coded secrets.
The agent's action is blocked before it can write the secret into your codebase.
The setup command: - Installs hooks or guardrails for the selected agent platform - Creates agentlint.yml with auto-detected settings (if it doesn't exist)
To remove AgentLint hooks:
agentlint uninstall
Create agentlint.yml in your project root (or run agentlint init):
```yaml
export AGENTCHUTE_API_URL=http://localhost:8000/v1 ```
When enabled, AgentLint sends privacy-safe event summaries only: file paths and lengths for writes/edits, truncated Bash command previews, truncated prompt previews, violation metadata, and rule counts. It never sends raw file contents, full edit strings, or full prompts.
agentlint import-agents-md --merge ```
When AGENTS.md exists and stack: auto is set, AgentLint also uses it for pack auto-detection.
agentlint doctor
Run any command-line tool as a PostToolUse check. AgentLint executes the command after Write/Edit and reports non-zero exit codes as violations:
rules:
cli-integration:
commands:
- name: ruff
on: ["Write", "Edit"]
glob: "**/*.py"
command: "ruff check {file.path} --output-format=concise"
timeout: 10
severity: warning
- name: pip-audit
on: ["Write", "Edit"]
glob: "**/requirements*.txt"
command: "pip-audit -r {file.path}"
timeout: 30
severity: warning
- name: pytest-related
on: ["Write", "Edit"]
glob: "src/**/*.py"
command: "pytest tests/ -k {file.stem} -x -q --tb=short"
timeout: 60
severity: info
Claude Code users can also install the marketplace wrapper from mauhpr/agentlint-plugin. The plugin repo contains Claude-specific marketplace metadata, hook files, and plugin commands; this repo contains the core engine and cross-platform setup.
AgentLint supports the AGENTS.md industry standard. Import conventions from your project's AGENTS.md into AgentLint config:
```bash
agentlint ci --diff origin/main...HEAD ```
name: AgentLint on: [pull_request] jobs: lint: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 with: { fetch-depth: 0 } - run: pip install agentlint - run: agentlint ci --diff origin/${{ github.base_ref }}...HEAD ```
Only ERROR violations fail the build. Warnings are reported but don't block. Use --format json for machine-readable output.
| Project | How AgentLint differs |
|---|---|
| guardrails-ai | Validates LLM I/O. AgentLint validates agent *tool calls* in real-time. |
| claude-code-guardrails | Uses external API. AgentLint is local-first, no network dependency. |
| Custom hooks | Copy-paste scripts. AgentLint is a composable engine with config + plugins. |
| Codacy Guardrails | Commercial, proprietary. AgentLint is fully open source. |
Does AgentLint slow down my AI coding agent? No. Rules evaluate in <10ms. AgentLint runs locally as a subprocess — no network calls, no API dependencies.
What if a rule is too strict for my project? Disable it in agentlint.yml: rules: { no-secrets: { enabled: false } }. Or switch to severity: relaxed to downgrade warnings to informational. The circuit breaker also helps — if a rule fires 3+ times in a session, it automatically degrades from blocking to advisory.
Is my code sent anywhere? No. AgentLint is fully offline by default. It reads the local hook, guardrail, MCP, or webhook payload and evaluates rules locally. No telemetry, no network requests. AgentChute sync is a separate opt-in path and sends only privacy-safe event summaries.
Can I use AgentLint outside Claude Code? Yes. AgentLint supports real-time blocking hooks on Claude Code, Cursor, Kimi, Grok, Gemini, Codex, and Continue.dev. For OpenAI Agents SDK and MCP hosts, use guardrail-based integration. The CLI also works standalone in any CI pipeline.
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,AI代码守护 在Agent工作流赛道中表现稳健,质量良好。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 | agentlint |
| 原始描述 | 开源AI工作流:Real-time guardrails for AI coding agents. 68 rules across 8 packs covering code。⭐21 · Python |
| Topics | ai-agentscode-qualitydeveloper-tools |
| GitHub | https://github.com/mauhpr/agentlint |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-26 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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