plano/skills/rules/cli-generate.md

title	impact	impactDescription	tags
Generate Prompt Targets from Python Functions with `planoai generate_prompt_targets`	MEDIUM	Manually writing prompt_targets YAML for existing Python APIs is error-prone — the generator introspects function signatures and produces correct YAML automatically	cli, generate, prompt-targets, python, code-generation

Generate Prompt Targets from Python Functions with planoai generate_prompt_targets

planoai generate_prompt_targets introspects Python function signatures and docstrings to generate prompt_targets YAML for your Plano config. This is the fastest way to expose existing Python APIs as LLM-callable functions without manually writing the YAML schema.

Python function requirements for generation:

• Use simple type annotations: int, float, bool, str, list, tuple, set, dict
• Include a docstring describing what the function does (becomes the description)
• Complex Pydantic models must be flattened into primitive typed parameters first

Example Python file:

# api.py

def get_stock_quote(symbol: str, exchange: str = "NYSE") -> dict:
    """Get the current stock price and trading data for a given stock symbol.

    Returns price, volume, market cap, and 24h change percentage.
    """
    # Implementation calls stock API
    pass

def get_weather_forecast(city: str, days: int = 3, units: str = "celsius") -> dict:
    """Get the weather forecast for a city.

    Returns temperature, precipitation, and conditions for the specified number of days.
    """
    pass

def search_flights(origin: str, destination: str, date: str, passengers: int = 1) -> list:
    """Search for available flights between two airports on a given date.

    Date format: YYYY-MM-DD. Returns list of flight options with prices.
    """
    pass

Running the generator:

planoai generate_prompt_targets --file api.py

Generated output (add to your config.yaml):

prompt_targets:
  - name: get_stock_quote
    description: Get the current stock price and trading data for a given stock symbol.
    parameters:
      - name: symbol
        type: str
        required: true
      - name: exchange
        type: str
        required: false
        default: NYSE
    # Add endpoint manually:
    endpoint:
      name: stock_api
      path: /quote?symbol={symbol}&exchange={exchange}

  - name: get_weather_forecast
    description: Get the weather forecast for a city.
    parameters:
      - name: city
        type: str
        required: true
      - name: days
        type: int
        required: false
        default: 3
      - name: units
        type: str
        required: false
        default: celsius
    endpoint:
      name: weather_api
      path: /forecast?city={city}&days={days}&units={units}

After generation, manually add the endpoint blocks pointing to your actual API. The generator produces the schema; you wire in the connectivity.

Reference: https://github.com/katanemo/archgw