skills/rules/cli-init.md
planoai init Templates to Bootstrap New Projects Correctlyplanoai init generates a valid config.yaml from built-in templates. Each template demonstrates a specific Plano capability with correct structure, realistic examples, and comments. Use this instead of writing config from scratch — it ensures you start with a valid, working configuration.
Available templates:
| Template ID | What It Demonstrates | Best For |
|---|---|---|
sub_agent_orchestration | Multi-agent routing with specialized sub-agents | Building agentic applications |
coding_agent_routing | Routing preferences + model aliases for coding workflows | Claude Code and coding assistants |
preference_aware_routing | Automatic LLM routing based on task type | Multi-model cost optimization |
filter_chain_guardrails | Input guards, query rewrite, context builder | RAG + safety pipelines |
conversational_state_v1_responses | Stateful conversations with memory | Chatbots, multi-turn assistants |
Usage:
# Initialize with a template
planoai init --template sub_agent_orchestration
# Initialize coding agent routing setup
planoai init --template coding_agent_routing
# Initialize a RAG with guardrails project
planoai init --template filter_chain_guardrails
Typical project setup workflow:
# 1. Create project directory
mkdir my-plano-agent && cd my-plano-agent
# 2. Bootstrap with the closest matching template
planoai init --template preference_aware_routing
# 3. Edit config.yaml to add your specific models, agents, and API keys
# (keys are already using $VAR substitution — just set your env vars)
# 4. Create .env file for local development
cat > .env << EOF
OPENAI_API_KEY=sk-proj-...
ANTHROPIC_API_KEY=sk-ant-...
EOF
echo ".env" >> .gitignore
# 5. Start Plano
planoai up
# 6. Test your configuration
curl http://localhost:12000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]}'
Start with preference_aware_routing for most LLM gateway use cases and sub_agent_orchestration for multi-agent applications. Both can be combined after you understand each independently.
Reference: https://github.com/katanemo/archgw