create-adk-agent

name	create-adk-agent
description	Generate a production-ready AI agent using Google ADK with Claude integration
model	sonnet

Create ADK Agent

I'll help you generate a production-ready AI agent using Google's Agent Development Kit (ADK) with Claude integration.

Information Needed

Please provide the following details:

1. Agent Name: What should we call your agent? (e.g., "linkedin-intelligence-agent")

2. Agent Purpose: What will this agent do? (e.g., "Research and qualify sales leads from LinkedIn")

3. Pattern Type:

   • react - Single agent with reasoning + acting loop
   • multi-agent - Team of specialized agents
   • workflow - Deterministic multi-step process

4. Tools Needed: Which tools should the agent use?

   • LinkedIn scraper
   • Apollo enrichment
   • Clearbit lookup
   • Email finder
   • Web search
   • Custom tools

5. LLM Model: Which Claude model?

   • claude-3-5-sonnet-20241022 (recommended for most tasks)
   • claude-3-haiku-20240307 (fast and cheap)
   • claude-3-5-opus-20241022 (most capable)

Generated Output

Based on your requirements, I will create:

1. Main Agent Implementation (agent.py)

   • Complete agent class with Claude integration
   • Tool initialization and management
   • Error handling and retry logic
   • Observability (logging, metrics)

2. Tool Implementations (tools/)

   • Custom tool classes
   • Input/output schemas
   • Rate limiting and caching

3. Configuration (config.yaml)

   • Agent settings
   • API keys and credentials
   • Behavior parameters

4. Tests (tests/)

   • Unit tests for agent logic
   • Integration tests for tools
   • End-to-end workflow tests

5. Deployment (Dockerfile, terraform/)

   • Container configuration
   • Cloud Run deployment
   • Kubernetes manifests

6. Documentation (README.md)

   • Setup instructions
   • Usage examples
   • API reference

Example Usage

# Initialize your agent
agent = YourAgent()

# Run the agent
result = await agent.run({
    "input": "your-data",
    "goal": "your-objective"
})

# Results include:
# - Observations from each step
# - Actions taken
# - Final synthesized output

Next Steps

After generation:

1. Install dependencies: pip install -r requirements.txt
2. Set environment variables in .env
3. Run tests: pytest tests/
4. Deploy: docker build && gcloud run deploy

Let me know your requirements and I'll generate the complete agent package!