Sandbox Execution Fallback

When to Use

Use this skill when

execute_code_sandbox

fails during Python code execution, particularly for tasks involving:

• Spreadsheet generation (xlsx, csv)
• Data processing and transformations
• File output operations
• Complex computations requiring libraries

Recovery Pattern

When

execute_code_sandbox

returns an error or fails to produce expected output:

Step 1: Write Python Code to File

Use

write_file

to save your Python script to a file:

# Use write_file tool with:
path: "script.py"
content: <your complete Python code as a string>

Step 2: Execute via Shell

Use

run_shell

to execute the script:

# Use run_shell tool with:
command: "python3 script.py"
timeout: <appropriate timeout, e.g., 300 for long-running tasks>

Step 3: Verify Output

Check the shell output for:

• Success messages or printed results
• Error messages (if any, diagnose and fix the script)
• File creation confirmations

Step 4: Access Generated Files

If the script creates output files (e.g., spreadsheets), they will be in the current working directory. Use

list_dir

to confirm, then

read_file

to access if needed.

Why This Works

• Same Python Environment:

  python3

  in the shell uses the same environment as the sandbox
• More Robust: Shell execution handles long-running or memory-intensive tasks better
• Debuggable: Errors are captured in stdout/stderr for easier diagnosis
• Identical Results: Produces the same output as sandbox execution when successful

Example: Spreadsheet Generation

Original code that failed in execute_code_sandbox:

import pandas as pd

data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)
df.to_excel('output.xlsx', index=False)
print("File created successfully")

Recovery Execution:

1. write_file

   with path="generate_spreadsheet.py" and the code above as content

2. run_shell

   with command="python3 generate_spreadsheet.py"
3. Verify output.xlsx was created with

   list_dir

Tips

• Increase

  timeout

  for complex operations (default 30s may be insufficient)
• Add explicit print statements for debugging
• Handle exceptions in your script and print error messages
• Clean up temporary script files after successful execution if needed