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Claude Automation Recommender

  • 355 installs
  • smithery.ai

This is a copy of claude-automation-recommender by anthropics - installs and ranking accrue to the original listing.

Use claude-automation-recommender for development tasks

About

claude-automation-recommender: A skill for development. This provides functionality for development workflows.

  • claude-automation-recommender

Claude Automation Recommender by the numbers

  • 355 all-time installs (skills.sh)
  • +2 installs in the week ending Jul 27, 2026 (Skillselion tracking)
  • Data as of Jul 27, 2026 (Skillselion catalog sync)
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Installs355
Repositorysmithery.ai

What it does

Use claude-automation-recommender for development tasks

Files

SKILL.mdMarkdownGitHub ↗

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|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.

## 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:*)"]
  }
}

Related skills

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