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安全護衛

使用此技能來防止在生產系統上工作或自主運行代理時發生破壞性操作。

安全護衛 是什麼?

安全護衛是一個 AI 代理技能,旨在通過攔截危險命令和限制文件編輯來防止對生產系統或自主代理工作流程的破壞性操作。它提供三種保護模式:小心模式(攔截並警告破壞性命令,如 `rm -rf` 或 `git push --force`)在執行前請求確認並建議更安全的替代方案;凍結模式(將文件編輯鎖定到指定目錄,如 `/safety-guard freeze src/components/`)阻止任何對該目錄之外的寫入;以及守衛模式(結合小心和凍結)如 `/safety-guard guard --dir src/api/ --allow-read-all`,允許隨意讀取但只允許寫入特定目錄並阻止所有地方的破壞性命令。解鎖使用 `/safety-guard off`。該實現通過 PreToolUse 鉤子攔截 Bash、Write、Edit 和 MultiEdit 工具調用,根據活動規則檢查命令或路徑,並將所有被阻止的操作記錄到 `~/.claude/safety-guard.log`。它默認啟用於 `codex -a never` 會話,並可與可觀測性風險評分配對以增強安全性。

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

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

安全護衛 — 防止破壞性操作

使用時機

  • 在生產系統上工作時
  • 代理自主運行時(全自動模式)
  • 想要限制編輯到特定目錄時
  • 敏感操作期間(遷移、部署、數據更改)

運作方式

三種保護模式:

模式 1:小心模式

在執行前攔截破壞性命令並發出警告:

監控的模式:
- rm -rf(尤其是 /、~ 或項目根目錄)
- git push --force
- git reset --hard
- git checkout .(丟棄所有變更)
- DROP TABLE / DROP DATABASE
- docker system prune
- kubectl delete
- chmod 777
- sudo rm
- npm publish(意外發佈)
- 任何帶有 --no-verify 的命令

當檢測到時:顯示命令的作用、請求確認、建議更安全的替代方案。

模式 2:凍結模式

將文件編輯鎖定到特定目錄樹:

/safety-guard freeze src/components/

任何在 src/components/ 之外的寫入/編輯都會被阻止並附上解釋。當你想要代理專注於某個區域而不觸摸無關代碼時很有用。

模式 3:守衛模式(小心 + 凍結組合)

同時啟用兩種保護。自主代理的最大安全性。

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

代理可以讀取任何內容,但只能寫入 src/api/。所有地方的破壞性命令都會被阻止。

解鎖

/safety-guard off

實現

使用 PreToolUse 鉤子來攔截 Bash、Write、Edit 和 MultiEdit 工具調用。在允許執行之前,根據活動規則檢查命令/路徑。

整合

  • 默認啟用於 codex -a never 會話
  • 與 ECC 2.0 中的可觀測性風險評分配對
  • 將所有被阻止的操作記錄到 ~/.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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