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Code Exec Fallback

  • 2 installs
  • 7.3k repo stars
  • Updated July 27, 2026
  • hkuds/openspace

Falls back to writing a Python script to file and running it via shell when execute_code_sandbox fails repeatedly.

About

Provides a fallback pattern for running Python code when execute_code_sandbox fails repeatedly: write the script to a file and execute it via shell instead. A developer uses it when the code sandbox hits environment limits, timeouts, or dependency issues.

  • Triggers after 2+ execute_code_sandbox failures
  • Writes script to file and runs via shell (run_shell python3)

Code Exec Fallback by the numbers

  • 2 all-time installs (skills.sh)
  • Ranked #464 of 597 Debugging skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/hkuds/openspace --skill code-exec-fallback

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Listed on Skillselion
Installs2
repo stars7.3k
Last updatedJuly 27, 2026
Repositoryhkuds/openspace

What it does

Falls back to writing a Python script to file and running it via shell when execute_code_sandbox fails repeatedly.

Files

SKILL.mdMarkdownGitHub ↗

Code Execution Fallback

When to Use

Use this pattern when execute_code_sandbox fails repeatedly (typically 2+ attempts) due to environment limitations, timeouts, dependency issues, or sandbox restrictions.

The Pattern

Instead of executing code directly in the sandbox, write the Python script to a file and execute it via shell:

1. Write the script using write_file 2. Execute via shell using run_shell with python3 script.py 3. Clean up (optional) remove the temporary file

Step-by-Step Instructions

Step 1: Write the Python Script

Use write_file to save your Python code:
- Path: Choose a descriptive name (e.g., "process_data.py", "analyze.py")
- Content: Your complete Python script with all imports and logic

Step 2: Execute via Shell

Use run_shell to execute:
- Command: "python3 <script_name>.py"
- Timeout: Set appropriately for your task (default 30s, increase if needed)

Step 3: Handle Output

- Capture stdout/stderr from run_shell
- Parse results as needed
- Optionally delete the script file after execution

Example

# Instead of this (which may fail):
execute_code_sandbox(code="import pandas as pd; df = pd.read_csv('data.csv')...")

# Do this:
write_file(path="analyze.py", content="""
import pandas as pd
import json

df = pd.read_csv('data.csv')
result = df.groupby('category').sum()
print(json.dumps(result.to_dict()))
""")

run_shell(command="python3 analyze.py", timeout=60)

Tips for Success

1. Include all imports in the script file - the shell environment may differ from the sandbox 2. Use absolute paths or ensure working directory is correct 3. Add error handling to your script for better debugging 4. Increase timeout for long-running operations (default is 30s) 5. Print structured output (JSON) if you need to parse results 6. Clean up temporary files after successful execution to avoid clutter

When This Helps

  • Sandbox has missing dependencies
  • Code execution times out in sandbox but would work in shell
  • File I/O operations are restricted in sandbox
  • Need to run external commands or system utilities
  • Complex multi-file projects that need proper file structure

Related skills

Debuggingbackend

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