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技能侦查员

在创建新技能之前,搜索本地、市场、GitHub和网络上的现有技能源。当用户想要为某个工作流创建、构建、派生或查找技能时使用。

技能侦查员 是什么?

这是一个AI助手技能,旨在防止重复造轮子。在用户打算创建新技能时,该技能会自动执行一套完整的搜索和评估流程:首先从本地已安装的技能和市场插件中查找,然后扩展到GitHub仓库和网络搜索,最后对外部来源进行安全审查。该技能支持Claude Code、Cursor、Codex等主流AI编码助手平台,通过6个步骤(捕获意图→搜索本地源→搜索远程源→审查外部匹配→排序结果→提供决策选项)来确保用户不会错过已有的社区解决方案。它的核心思想是“先搜索再构建”,在用户选择“创建新技能”之前,必须已经充分搜索并确认没有合适的现有技能。这对于维护大型技能库、避免技能碎片化、以及确保外部技能的安全性都至关重要。该技能由社区贡献,在PR #1232中被引入,由redminwang维护。

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

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

技能侦查员 是做什么的?

在创建新技能之前使用此技能。目标是避免重复已有的社区或市场工作,同时在使用任何外部内容前进行审查。

来源:来自社区 PR #1232,由 redminwang 保存。

什么时候使用

  • 用户说“创建技能”、“构建技能”、“制作技能”或“新技能”。
  • 用户问“有没有适用于 X 的技能?”或“是否存在能做 Y 的技能?”
  • 用户描述一个工作流,而你正要建议创建一个新技能。
  • 用户想要派生或扩展现有技能。

如果用户明确表示要跳过搜索或从头创建,确认该请求并继续执行所要求的创建工作流。

工作原理

步骤 1 - 捕获意图

提取:

  • 技能应该执行的任务。
  • 使用技能的触发条件。
  • 涉及的领域、工具、框架或数据源。
  • 三到五个搜索关键词以及有用的同义词。

步骤 2 - 搜索本地源

首先搜索已安装的技能和市场技能名称。本地源更受青睐,因为它们已存在于用户的环境中。

find ~/.claude/skills -maxdepth 2 -name SKILL.md 2>/dev/null | grep -iE "keyword|synonym"
find ~/.claude/plugins/marketplaces -path '*/skills/*/SKILL.md' 2>/dev/null | grep -iE "keyword|synonym"

然后搜索前置描述:

grep -RilE "keyword|synonym" ~/.claude/skills ~/.claude/plugins/marketplaces 2>/dev/null

步骤 3 - 搜索远程源

使用可用的 GitHub 和网络搜索工具。优先使用简洁的查询:

gh search repos "claude code skill keyword" --limit 10 --sort stars
gh search code "name: keyword" --filename SKILL.md --limit 10

对于网络搜索,最多使用三个有针对性的查询,例如:

"claude code skill" keyword
"SKILL.md" keyword
"everything-claude-code" keyword

步骤 4 - 审查外部匹配项

在推荐任何外部技能供采用或派生之前:

  • 阅读 SKILL.md 的前置信息和说明。
  • 检查是否有意外的 shell 命令、文件写入、网络调用、凭证处理或软件包安装。
  • 检查仓库是否似乎仍在维护。
  • 更倾向于复制到一个新的本地分支并审查差异,而不是直接编辑市场原始文件。

步骤 5 - 对结果排序

按以下标准对候选排序:

  1. 技能名称中的精确关键词匹配。
  2. 描述中的关键词或同义词匹配。
  3. 本地已安装或市场来源。
  4. 有近期活动的已维护 GitHub 来源。
  5. 仅限网络提及。

最终列表上限为 10 个结果。

步骤 6 - 提供决策选项

给用户一个简短的表格:

选项含义
使用现有按原样调用或安装匹配的技能。
派生或扩展复制最接近的技能并进行修改。
新建在确认没有接近匹配项后,构建一个新技能。

只有在用户选择了该路径,或者搜索没有找到接近匹配项之后,才创建新技能。

示例

结果表格

| # | 技能 | 来源 | 匹配原因 | 差距 |
| --- | --- | --- | --- | --- |
| 1 | article-writing | 本地 ECC | 草拟文章和指南 | 不专注于发布说明 |
| 2 | content-engine | 本地 ECC | 多格式内容工作流 | 比需要的更复杂 |
| 3 | blog-writer | GitHub | 博客写作技能,有近期提交 | 需要安全审查 |

面向用户的总结

我找到了两个接近的本地匹配和一个外部候选。最接近的是 `article-writing`;它涵盖了起草和修订,但不包含您要求的发布说明清单。我可以直接使用它,将其派生为发布说明变体,或者创建一个全新的技能。

反模式

  • 在可以进行合理搜索时,不要直接跳到新建技能。
  • 没有先阅读外部技能就安装它们。
  • 不要呈现一长串未排序的弱匹配项。
  • 不要将仅限网络提及视为可信来源。
  • 不要直接编辑已安装的市场原始文件。

相关

  • search-first - 在构建之前先进行搜索的通用工作流。
  • skill-stocktake - 审计已安装技能的健康状况、重复项和缺口。
  • agent-sort - 对现有代理和技能进行分类和整理。

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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