plano/skills/rules/cli-generate.md

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---
title: Generate Prompt Targets from Python Functions with `planoai generate_prompt_targets`
impact: MEDIUM
impactDescription: Manually writing prompt_targets YAML for existing Python APIs is error-prone — the generator introspects function signatures and produces correct YAML automatically
tags: 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:**
```python
# 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:**
```bash
planoai generate_prompt_targets --file api.py
```
**Generated output (add to your config.yaml):**
```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