# Set Up Workflow: Claude Code Production Infrastructure: Auto-Activating Skills & Agents
## What This Is
This is a production-ready toolkit for the Claude Code AI assistant that makes its special abilities (skills) activate automatically when needed. It provides a library of pre-built configurations, hooks, and agent personas to make the AI more proactive and effective in a professional development environment.
Source: https://github.com/diet103/claude-code-infrastructure-showcase
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
- Whether this repository or a similar tool is already cloned or installed
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Fetch the Source
Clone or inspect the repository to understand what needs to be installed:
```bash
gh repo clone diet103/claude-code-infrastructure-showcase
```
Review the README, directory structure, and any install instructions before proceeding.
## What to Implement
This is an **AI Workflow** — an end-to-end automation pattern or integration pipeline.
- Study the workflow architecture from the source and context below
- Identify which parts I can implement locally vs. parts that need external services
- For local parts: implement them using my existing stack and API keys
- For external parts: tell me exactly what services I need and help me configure the integration code
- Wire up any required API calls using keys from my .env files
## Additional Context
- Clone the repository 'https://github.com/diet103/claude-code-infrastructure-showcase' into a temporary directory to serve as a reference.
- Scan the user's project to identify their primary languages (e.g., TypeScript, React) and then recommend the most relevant components from the showcase, starting with the auto-activation hooks in '.claude/hooks/'.
- Once the user confirms, copy the selected hook and skill files into the user's active project's '.claude/' directory, creating it if necessary, and merge the showcase's 'skill-rules.json' with any existing rules to enable auto-activation.
## Reference Implementation
```
```
skill-name/
SKILL.md # <500 lines, high-level guide
resources/
topic-1.md # <500 lines each
topic-2.md
topic-3.md
```
```
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it