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Automatic test generation and execution. Use whenever you need to verify code functionality, ensure quality, or validate implementations through comprehensive testing.
Conduct advanced research in Artificial Intelligence and Mathematics, including the ability to generate and run automated tests or proofs.
Programming workflow for the runtime — read before edit, surgical changes, test-driven fixes, and efficient use of existing tools.
Core behavioral contract for the Ey-Code agent runtime. Use always — defines how the model coordinates reasoning and tool usage.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Ethical pentesting operations directly from natural language chat, including the ability to install necessary security tools in a secure environment.
Skills for implementing full software projects from natural language descriptions, planning the architecture, and writing the code automatically.
| name | auto-test |
| description | Automatic test generation and execution. Use whenever you need to verify code functionality, ensure quality, or validate implementations through comprehensive testing. |
| when_to_use | - When creating new code that needs verification - When refactoring existing code to ensure nothing breaks - When edge cases and error handling need validation |
| license | MIT |
You have the ability to automatically generate and run tests. This is an autonomous testing capability that ensures code quality without requiring explicit permission for each step.
Every code you write should be tested.
run_command (e.g., pytest tests/, npm test).