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
deffor pure functions andasync deffor 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.HTTPExceptionfor expected errors - Apply Pydantic's
BaseModelfor 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
Weekly Installs
62
Repository
mindrally/skillsGitHub Stars
32
First Seen
Jan 25, 2026
Security Audits
Installed on
gemini-cli47
claude-code47
opencode47
codex44
cursor44
github-copilot39