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Claude Automation Recommender

OrganizationPopular
anthropics
claude-automation-recommender

Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.

Overview

Publisheranthropics
Repositoryclaude-plugins-official
Skill nameclaude-automation-recommender
Stars
36.4K
Forks
4.1K
Bundled files
5
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Claude Automation Recommender AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/claude-plugins-official.git /tmp/claude-plugins-official
mkdir -p .claude/skills
cp -r /tmp/claude-plugins-official/plugins/claude-code-setup/skills/claude-automation-recommender .claude/skills/claude-automation-recommender
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Claude Automation Recommender in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Claude Automation Recommender on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Claude Automation Recommender is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

bash
# 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|convex|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, Convex, raw SQLDatabase / backend 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
Uses ConvexConvex MCP - Live deployment introspection, run queries/mutations, manage env vars and logs
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.

markdown
## 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)
```yaml
---
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:

```bash
# 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:

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Claude Automation Recommender AI skill do?

Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.

Why use Claude Automation Recommender on TypingMind?

Because you install it once and use it with any model. Claude Automation Recommender is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Claude Automation Recommender in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/claude-plugins-official/tree/main/plugins/claude-code-setup/skills/claude-automation-recommender. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Claude Automation Recommender?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Claude Automation Recommender?

As many as you like. As long as a model supports skills, you can use Claude Automation Recommender with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Claude Automation Recommender AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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