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安全护卫

用于防止在生产系统上操作或自主运行代理时发生破坏性行为。

安全护卫 是什么?

安全护卫(Safety Guard)是一项 AI 代理技能,旨在防止在操作生产系统或代理以全自动模式自主运行时发生破坏性操作。该技能提供三种保护模式:谨慎模式(Careful Mode)会拦截并警告高风险命令(如 `rm -rf`、`git push --force`、`DROP TABLE`),在每次执行前请求确认;冻结模式(Freeze Mode)将文件编辑锁定到指定的目录树(如 `src/components/`),任何超出该范围的写入尝试都将被阻止;护卫模式(Guard Mode)则结合了前两种模式,既限制写入范围又拦截破坏性命令。该技能通过 PreToolUse 钩子拦截 Bash、Write、Edit 和 MultiEdit 工具调用,并支持通过配置文件(如 `~/.claude/safety-guard.log`)记录所有阻止的操作。支持平台包括 Claude Code、Codex 以及其他兼容 CLM 协议的 AI 代理环境。此技能特别适合与代码审查、变更管理 CI 集成等工具配合使用,为生产环境提供安全保障。

兼容平台✓Claude Code✓Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/safety-guard

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

安全护卫 — 防止破坏性操作

使用时机

  • 在生产系统上工作时
  • 代理自主运行(全自动模式)时
  • 想要将编辑限制到特定目录时
  • 在执行敏感操作期间(迁移、部署、数据变更)

工作原理

三种保护模式:

模式 1:谨慎模式

在执行前拦截破坏性命令并发出警告:

监护模式:
- rm -rf(尤其是 /、~ 或项目根目录)
- git push --force
- git reset --hard
- git checkout .(丢弃所有更改)
- DROP TABLE / DROP DATABASE
- docker system prune
- kubectl delete
- chmod 777
- sudo rm
- npm publish(意外发布)
- 任何带有 --no-verify 的命令

检测到时:显示该命令将执行的操作,请求确认,并建议更安全的替代方案。

模式 2:冻结模式

将文件编辑锁定到特定的目录树:

/safety-guard freeze src/components/

任何对 src/components/ 之外的写入/编辑操作都会被阻止并附带说明。当您希望代理专注于一个区域而不触及无关代码时非常有用。

模式 3:护卫模式(谨慎 + 冻结组合)

同时启用两种保护。为自主代理提供最大安全性。

/safety-guard guard --dir src/api/ --allow-read-all

代理可以读取任何内容,但只能写入 src/api/。破坏性命令在所有位置都被阻止。

解锁

/safety-guard off

实现

使用 PreToolUse 钩子拦截 Bash、Write、Edit 和 MultiEdit 工具调用。在允许执行之前,根据活动规则检查命令/路径。

集成

  • 默认在 codex -a never 会话中启用
  • 与 ECC 2.0 中的可观测性风险评分配合使用
  • 将所有被阻止的操作记录到 ~/.claude/safety-guard.log

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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