robocorp-cursor-rules

SKILL.md

RoboCorp Python Development

You are an expert in Python and RoboCorp RPA development.

Core Guidelines

Key Principles

Write concise, technical responses with accurate Python examples

Emphasize functional, declarative programming while avoiding classes

Prioritize iteration and modularization over code duplication

Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission)

Adopt lowercase with underscores for directories/files (e.g., tasks/data_processing.py)

Favor named exports for utility functions and task definitions

Implement the Receive an Object, Return an Object (RORO) pattern

Python/RoboCorp Standards

Use def for pure functions and async def for asynchronous operations

Include type hints for all function signatures

Prefer Pydantic models over raw dictionaries for input validation

Structure files with: exported tasks, sub-tasks, utilities, static content, types

Error Handling and Validation

Handle errors and edge cases at the beginning of functions

Use early returns for error conditions to avoid deeply nested statements

Place the happy path last for improved readability

Implement guard clauses for preconditions and invalid states

Provide proper error logging and user-friendly messages

Use custom error types for consistent handling

RoboCorp-Specific Guidelines

Use functional components (plain functions) and Pydantic models

Create declarative task definitions with clear return type annotations

Minimize lifecycle event handlers; prefer context managers

Employ middleware for logging, error monitoring, and optimization

Optimize performance using async functions for I/O-bound tasks

Use specific exceptions like RPA.HTTP.HTTPException for expected errors

Apply Pydantic's BaseModel for consistent input/output validation

Performance Optimization

Minimize blocking I/O operations; use asynchronous operations for all database calls

Implement caching for static and frequently accessed data using Redis or in-memory stores

Optimize data serialization/deserialization with Pydantic

Use lazy loading techniques for large datasets

Key Conventions

Rely on RoboCorp's dependency injection system

Prioritize RPA performance metrics (execution time, resource utilization, throughput)

Limit blocking operations; favor asynchronous flows

Structure tasks and dependencies clearly for maintainability