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Agent Skill · 研究检索

anthropics-claude-automation-recommender(Anthropic Claude 自动化 recommender)

anthropics-claude-automation-recommender 用于查找、检索和筛选相关信息,适合在 Local Agent 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

anthropics-claude-automation-recommender 是研究检索类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为操作浏览器;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 53,999。

总安装 517周安装 22下载 181核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:anthropics-claude-automation-recommender(Anthropic Claude 自动化 recommender)
来源仓库:https://smithery.ai
仓库路径:anthropics-claude-automation-recommender
安装命令:
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

分析代码库模式并推荐 Claude Code 自动化扩展方案,提升开发效率。适用于希望优化本地工作流的中大型项目,聚焦高频重复任务。输出为只读建议,不包含文件修改,需用户自行实施或进一步请求协助。推荐范围涵盖命令、钩子与集成三类,每次聚焦 1–2 个高价值项。建议结合项目规模选择优先级,避免一次性引入过多变更点。

来源仓库内路径:anthropics-claude-automation-recommender

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Local Agent;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 anthropics-claude-automation-recommender。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

anthropics-claude-automation-recommender 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 anthropics-claude-automation-recommender。

anthropics-claude-automation-recommender 支持哪些 AI 工具?

公开资料标注支持 Local Agent。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

anthropics-claude-automation-recommender 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

anthropics-claude-automation-recommender 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

anthropics-claude-automation-recommender 用的人多吗?

公开数据是累计安装 517 次,近一周安装 22 次,下载 181 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

anthropics-claude-automation-recommender 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Local Agent,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
anthropics-claude-automation-recommender

Anthropic Claude 自动化 recommender · 本页

517—操作浏览器未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Claude Automation Recommender

Analyze codebase patterns to recommend tailored Claude Code automations across all extensibility options.

This skill is read-only. It analyzes the codebase and outputs recommendations. It does NOT create or modify any files. Users implement the recommendations themselves or ask Claude separately to help build them.

Output Guidelines

  • Recommend 1-2 of each type: Don't overwhelm - surface the top 1-2 most valuable automations per category
  • If user asks for a specific type: Focus only on that type and provide more options (3-5 recommendations)
  • Go beyond the reference lists: The reference files contain common patterns, but use web search to find recommendations specific to the codebase's tools, frameworks, and libraries
  • Tell users they can ask for more: End by noting they can request more recommendations for any specific category

Automation Types Overview

TypeBest For
HooksAutomatic actions on tool events (format on save, lint, block edits)
SubagentsSpecialized reviewers/analyzers that run in parallel
SkillsPackaged expertise, workflows, and repeatable tasks (invoked by Claude or user via /skill-name)
PluginsCollections of skills that can be installed
MCP ServersExternal tool integrations (databases, APIs, browsers, docs)

Workflow

Phase 1: Codebase Analysis

Gather project context:

# Detect project type and tools
ls -la package.json pyproject.toml Cargo.toml go.mod pom.xml 2>/dev/null
cat package.json 2>/dev/null | head -50

# Check dependencies for MCP server recommendations
cat package.json 2>/dev/null | grep -E '"(react|vue|angular|next|express|fastapi|django|prisma|supabase|stripe)"'

# Check for existing Claude Code config
ls -la .claude/ CLAUDE.md 2>/dev/null

# Analyze project structure
ls -la src/ app/ lib/ tests/ components/ pages/ api/ 2>/dev/null

Key Indicators to Capture:

CategoryWhat to Look ForInforms Recommendations For
Language/Frameworkpackage.json, pyproject.toml, import patternsHooks, MCP servers
Frontend stackReact, Vue, Angular, Next.jsPlaywright MCP, frontend skills
Backend stackExpress, FastAPI, DjangoAPI documentation tools
DatabasePrisma, Supabase, raw SQLDatabase MCP servers
External APIsStripe, OpenAI, AWS SDKscontext7 MCP for docs
TestingJest, pytest, Playwright configsTesting hooks, subagents
CI/CDGitHub Actions, CircleCIGitHub MCP server
Issue trackingLinear, Jira referencesIssue tracker MCP
Docs patternsOpenAPI, JSDoc, docstringsDocumentation skills

Phase 2: Generate Recommendations

Based on analysis, generate recommendations across all categories:

A. MCP Server Recommendations

See references/mcp-servers.md for detailed patterns.

Codebase SignalRecommended MCP Server
Uses popular libraries (React, Express, etc.)context7 - Live documentation lookup
Frontend with UI testing needsPlaywright - Browser automation/testing
Uses SupabaseSupabase MCP - Direct database operations
PostgreSQL/MySQL databaseDatabase MCP - Query and schema tools
GitHub repositoryGitHub MCP - Issues, PRs, actions
Uses Linear for issuesLinear MCP - Issue management
AWS infrastructureAWS MCP - Cloud resource management
Slack workspaceSlack MCP - Team notifications
Memory/context persistenceMemory MCP - Cross-session memory
Sentry error trackingSentry MCP - Error investigation
Docker containersDocker MCP - Container management
B. Skills Recommendations

See references/skills-reference.md for details.

Create skills in .claude/skills/<name>/SKILL.md. Some are also available via plugins:

Codebase SignalSkillPlugin
Building pluginsskill-developmentplugin-dev
Git commitscommitcommit-commands
React/Vue/Angularfrontend-designfrontend-design
Automation ruleswriting-ruleshookify
Feature planningfeature-devfeature-dev

Custom skills to create (with templates, scripts, examples):

Codebase SignalSkill to CreateInvocation
API routesapi-doc (with OpenAPI template)Both
Database projectcreate-migration (with validation script)User-only
Test suitegen-test (with example tests)User-only
Component librarynew-component (with templates)User-only
PR workflowpr-check (with checklist)User-only
Releasesrelease-notes (with git context)User-only
Code styleproject-conventionsClaude-only
Onboardingsetup-dev (with prereq script)User-only
C. Hooks Recommendations

See references/hooks-patterns.md for configurations.

Codebase SignalRecommended Hook
Prettier configuredPostToolUse: auto-format on edit
ESLint/Ruff configuredPostToolUse: auto-lint on edit
TypeScript projectPostToolUse: type-check on edit
Tests directory existsPostToolUse: run related tests
.env files presentPreToolUse: block .env edits
Lock files presentPreToolUse: block lock file edits
Security-sensitive codePreToolUse: require confirmation
D. Subagent Recommendations

See references/subagent-templates.md for templates.

Codebase SignalRecommended Subagent
Large codebase (>500 files)code-reviewer - Parallel code review
Auth/payments codesecurity-reviewer - Security audits
API projectapi-documenter - OpenAPI generation
Performance criticalperformance-analyzer - Bottleneck detection
Frontend heavyui-reviewer - Accessibility review
Needs more teststest-writer - Test generation
E. Plugin Recommendations

See references/plugins-reference.md for available plugins.

Codebase SignalRecommended Plugin
General productivityanthropic-agent-skills - Core skills bundle
Document workflowsInstall docx, xlsx, pdf skills
Frontend developmentfrontend-design plugin
Building AI toolsmcp-builder for MCP development

Phase 3: Output Recommendations Report

Format recommendations clearly. Only include 1-2 recommendations per category - the most valuable ones for this specific codebase. Skip categories that aren't relevant.

## Claude Code Automation Recommendations

I've analyzed your codebase and identified the top automations for each category. Here are my top 1-2 recommendations per type:

### Codebase Profile
- **Type**: [detected language/runtime]
- **Framework**: [detected framework]
- **Key Libraries**: [relevant libraries detected]

---

### 🔌 MCP Servers

#### context7
**Why**: [specific reason based on detected libraries]
**Install**: `claude mcp add context7`

---

### 🎯 Skills

#### [skill name]
**Why**: [specific reason]
**Create**: `.claude/skills/[name]/SKILL.md`
**Invocation**: User-only / Both / Claude-only
**Also available in**: [plugin-name] plugin (if applicable)

name: [skill-name] description: [what it does] disable-model-invocation: true # for user-only



---

### ⚡ Hooks

#### [hook name]

**Why**: [specific reason based on detected config] **Where**: `.claude/settings.json`

---

### 🤖 Subagents

#### [agent name]

**Why**: [specific reason based on codebase patterns] **Where**: `.claude/agents/[name].md`

---

**Want more?** Ask for additional recommendations for any specific category (e.g., "show me more MCP server options" or "what other hooks would help?").

**Want help implementing any of these?** Just ask and I can help you set up any of the recommendations above.

Decision Framework

When to Recommend MCP Servers

  • External service integration needed (databases, APIs)
  • Documentation lookup for libraries/SDKs
  • Browser automation or testing
  • Team tool integration (GitHub, Linear, Slack)
  • Cloud infrastructure management

When to Recommend Skills

  • Document generation (docx, xlsx, pptx, pdf — also in plugins)
  • Frequently repeated prompts or workflows
  • Project-specific tasks with arguments
  • Applying templates or scripts to tasks (skills can bundle supporting files)
  • Quick actions invoked with /skill-name
  • Workflows that should run in isolation (context: fork)

Invocation control:

  • disable-model-invocation: true — User-only (for side effects: deploy, commit, send)
  • user-invocable: false — Claude-only (for background knowledge)
  • Default (omit both) — Both can invoke

When to Recommend Hooks

  • Repetitive post-edit actions (formatting, linting)
  • Protection rules (block sensitive file edits)
  • Validation checks (tests, type checks)

When to Recommend Subagents

  • Specialized expertise needed (security, performance)
  • Parallel review workflows
  • Background quality checks

When to Recommend Plugins

  • Need multiple related skills
  • Want pre-packaged automation bundles
  • Team-wide standardization

Configuration Tips

MCP Server Setup

Team sharing: Check .mcp.json into repo so entire team gets same MCP servers

Debugging: Use --mcp-debug flag to identify configuration issues

Prerequisites to recommend:

  • GitHub CLI (gh) - enables native GitHub operations
  • Puppeteer/Playwright CLI - for browser MCP servers

Headless Mode (for CI/Automation)

Recommend headless Claude for automated pipelines:

# Pre-commit hook example
claude -p "fix lint errors in src/" --allowedTools Edit,Write

# CI pipeline with structured output
claude -p "<prompt>" --output-format stream-json | your_command

Permissions for Hooks

Configure allowed tools in .claude/settings.json:

{
  "permissions": {
    "allow": ["Edit", "Write", "Bash(npm test:*)", "Bash(git commit:*)"]
  }
}

平台分布

Local Agent

78.53%
按下载量换算142

安全审计

Socket

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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