Robocorp Cursor Rules

by mindrally97184105b5daNo license269 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 5 weeks ago

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

Instructions onlySoftware Development
AI-generated overview

Coding guidelines for building RoboCorp RPA automation in Python with functional style, Pydantic validation and async operations.

What it does
Provides a set of development conventions for writing RoboCorp RPA automation in Python. It covers functional and declarative programming, type hints, Pydantic models for input and output validation, error handling with guard clauses and custom exceptions, async I/O, caching, and RoboCorp-specific practices such as dependency injection and declarative task definitions. It produces guidance only, not runnable code or generated files.
When to use it
Use it when writing or reviewing Python code for RoboCorp RPA projects and you want consistent structure, validation and async conventions. It is aimed at developers who need a shared style reference for tasks, utilities and error handling.
Requirements
No tools, packages or credentials are required; it is an instructions-only document with no scripts.

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

  1. Rely on RoboCorp's dependency injection system
  2. Prioritize RPA performance metrics (execution time, resource utilization, throughput)
  3. Limit blocking operations; favor asynchronous flows
  4. Structure tasks and dependencies clearly for maintainability

Source and attribution

Source:mindrally/skillsinrobocorp-cursor-rulesat commit9718410

License: No license

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