メニュー
Programming workflow for the runtime — read before edit, surgical changes, test-driven fixes, and efficient use of existing tools.
Conduct advanced research in Artificial Intelligence and Mathematics, including the ability to generate and run automated tests or proofs.
Automatic test generation and execution. Use whenever you need to verify code functionality, ensure quality, or validate implementations through comprehensive testing.
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 | coding-agent |
| description | Programming workflow for the runtime — read before edit, surgical changes, test-driven fixes, and efficient use of existing tools. |
| when_to_use | - User asks to write, edit, refactor, debug, or test code. - User asks to review a file or diff. |
| license | MIT |
list_dir, grep_search to find relevant files.read_file before any edit. Never edit blind or assume line numbers.replace_file_content or multi_replace_file_content. Change only the lines the task requires. Do not rewrite entire files unless completely necessary.run_command to execute tests, linters, or syntax checks (python -m py_compile ...).file:line and briefly summarize what changed.grep_search.view_file, list_dir, grep_search.replace_file_content, multi_replace_file_content, write_to_file.run_command (for tests or syntax checks).run_command to stage and commit when asked.