robocorp-cursor-rules

•

6155 months ago

Guidelines for building RoboCorp RPA automation with Python, emphasizing functional programming, Pydantic validation, and async operations.

Quick Install

npxskills add mindrally/skills--skill robocorp-cursor-rules

Instructions

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

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