lamm-mit/code-execution

Code Execution Skill

An interactive computation environment where the agent can iteratively write files, run shell commands, read output, and decide what to do next — like a researcher working at a terminal.

This is NOT a single-script skill. It provides an agentic loop with three actions:

Available Actions

write_file

Write content to a file (Python scripts, SLURM submission scripts, etc.)

{"action": "write_file", "path": "relax.py", "content": "import ..."}

run_command

Execute a shell command and observe the output.

{"action": "run_command", "command": "python3 relax.py"}

{"action": "run_command", "command": "sbatch submit.sh"}

{"action": "run_command", "command": "squeue -u $USER"}

{"action": "run_command", "command": "cat results.json"}

done

Signal that the computation is complete and return results.

{"action": "done", "result": {"status": "completed", "findings": [...]}}

Typical Workflow

1. Write a Python script that generates structures
2. Run it
3. Write a SLURM submission script for GPU work
4. Submit with sbatch
5. Check status with squeue or sacct
6. Read results with cat
7. Analyze and report

Guidelines

• Refer to other skills' SKILL.md for API documentation (UMA, HPC, materials)
• Print progress to stderr, final results to stdout as JSON
• For GPU work: write a self-contained Python script, wrap it in a SLURM script, submit with sbatch
• Check job status before reading results
• Each action gets one response — plan each step carefully