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code-exec-fallback-266cba

Recover from repeated sandbox execution failures by saving Python code to a script and running it through run_shell. Check output, error messages, and exit codes to confirm results or diagnose remaining execution problems.

OriginalShow the original description

Fallback workflow for reliable code execution when sandbox fails repeatedly

See how to install

Good for

  • Continuing Python work after two consecutive sandbox failures
  • Switching execution methods after persistent timeouts
  • Diagnosing script failures through error output
  • Setting longer timeouts for heavy processing

Files included (2)

  • SKILL.md2.5 KB
  • .skill_id39 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Code Execution Fallback Pattern

When to Use This Skill

Apply this pattern when you encounter repeated failures with execute_code_sandbox:

  • 2+ consecutive failures with opaque or unknown errors
  • Timeout errors that persist across retry attempts
  • Environment-related errors that don't resolve with code fixes

The Fallback Workflow

Step 1: Detect Repeated Failures

Track execution failures. After 2 consecutive failures with execute_code_sandbox, switch to the fallback approach.

Step 2: Write Script to File

Use write_file to save your Python script:

write_file(
    path="/workspace/script_name.py",
    content="# Your Python code here\nimport sys\n..."
)

Step 3: Execute via Shell

Use run_shell to run the script:

run_shell(
    command="python /workspace/script_name.py",
    timeout=300
)

Step 4: Capture Output

Parse stdout/stderr from run_shell output to verify success or diagnose issues.

Complete Example

# Instead of this (which may fail):
result = execute_code_sandbox(code="import pandas as pd\n...")

# Use this fallback pattern:
script_content = """
import pandas as pd
import sys

try:
    # Your logic here
    df = pd.DataFrame({'col': [1, 2, 3]})
    print(df.to_csv())
    sys.exit(0)
except Exception as e:
    print(f"ERROR: {e}", file=sys.stderr)
    sys.exit(1)
"""

# Write the script
write_file(path="/workspace/my_script.py", content=script_content)

# Execute via shell
result = run_shell(command="python /workspace/my_script.py", timeout=300)

Best Practices

  1. Add error handling in your script - use try/except with sys.exit() codes
  2. Set appropriate timeouts - run_shell default is 30s, increase for heavy operations
  3. Clean up temporary files after execution if needed
  4. Log the fallback trigger - document why you switched approaches
  5. Verify Python availability - Most sandboxes have Python 3.x by default

Why This Works

  • write_file is more reliable for file I/O operations
  • run_shell gives you direct control over execution environment
  • Shell execution bypasses sandbox serialization issues
  • Better error visibility through stdout/stderr streams

When NOT to Use This Pattern

  • First-time execution failures (retry the sandbox first)
  • Simple one-liner code (sandbox is faster)
  • When sandbox errors are clearly code bugs (fix the code instead)
  • Security-sensitive operations requiring sandbox isolation

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