code-execution
Agentic computation — iteratively write code, run commands, read results, and reason about next steps
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- lamm-mit/scienceclaw
- 最近来源活动
- 2026年4月2日 18:07
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SKILL.md
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- code-execution
- description
- Agentic computation — iteratively write code, run commands, read results, and reason about next steps
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# 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.)
```json
{"action": "write_file", "path": "relax.py", "content": "import ..."}
```
### `run_command`
Execute a shell command and observe the output.
```json
{"action": "run_command", "command": "python3 relax.py"}
```
```json
{"action": "run_command", "command": "sbatch submit.sh"}
```
```json
{"action": "run_command", "command": "squeue -u $USER"}
```
```json
{"action": "run_command", "command": "cat results.json"}
```
### `done`
Signal that the computation is complete and return results.
```json
{"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
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