OpenSpace run-shell-fallback
Use run_shell with inline Python as a reliable fallback when execute_code_sandbox or read_file fail
git clone https://github.com/HKUDS/OpenSpace
T=$(mktemp -d) && git clone --depth=1 https://github.com/HKUDS/OpenSpace "$T" && mkdir -p ~/.claude/skills && cp -r "$T/gdpval_bench/skills/run-shell-fallback" ~/.claude/skills/hkuds-openspace-run-shell-fallback && rm -rf "$T"
gdpval_bench/skills/run-shell-fallback/SKILL.mdRun Shell Fallback Pattern
This skill provides a reliable workaround when
execute_code_sandbox or read_file fail with 'unknown error' by switching to run_shell with inline Python code.
When to Use
Apply this pattern when you encounter:
fails with "unknown error" or timeoutexecute_code_sandbox
fails to read accessible files with "unknown error"read_file- Sandbox environment is unreliable for your specific task
How to Implement
1. File Reading Fallback
When
read_file fails, use run_shell with Python or cat:
For text files:
run_shell(command="cat /path/to/file.txt")
For structured parsing (Python one-liner):
run_shell(command="python3 -c \"import json; print(json.load(open('/path/to/file.json')))\"")
For multi-line Python processing:
run_shell(command="python3 << 'EOF' with open('/path/to/file.txt', 'r') as f: content = f.read() # Process content here print(content.upper()) EOF")
2. Code Execution Fallback
When
execute_code_sandbox fails, use run_shell with inline Python:
Simple one-liners:
run_shell(command="python3 -c \"print('Hello'); import os; print(os.getcwd())\"")
Multi-line scripts (heredoc):
run_shell(command="python3 << 'EOF' import os import json def process_data(data): return {k: v.upper() if isinstance(v, str) else v for k, v in data.items()} with open('input.json') as f: data = json.load(f) result = process_data(data) print(json.dumps(result, indent=2)) EOF")
With inline file write:
run_shell(command="python3 << 'EOF' result = {'status': 'success', 'count': 42} with open('output.json', 'w') as f: json.dump(result, f, indent=2) print('File written successfully') EOF")
3. Decision Flow
1. Attempt execute_code_sandbox or read_file 2. If failure with 'unknown error': a. Determine task type (code execution vs file reading) b. Choose inline Python approach (-c for simple, heredoc for complex) c. Execute via run_shell d. Parse output as needed 3. Continue with task using results from run_shell
Best Practices
-
Escape quotes properly in
commands: Use-c
for double quotes inside the command string\" -
Use heredoc for complex scripts: When code exceeds 2-3 lines or needs multiple imports, use
syntax<< 'EOF' -
Quote EOF marker: Use
(with quotes) to prevent variable expansion in the heredoc<< 'EOF' -
Capture stdout: Design your inline Python to print results to stdout for easy capture
-
Error handling: Add try/except blocks in your inline Python to catch and report errors clearly
-
File paths: Use absolute paths when possible, or ensure working directory is correct
Examples
Example 1: Read and parse JSON after read_file failure
run_shell(command="python3 -c \"import json; data=json.load(open('config.json')); print(data['key'])\"")
Example 2: Process CSV data after execute_code_sandbox failure
run_shell(command="python3 << 'EOF' import csv with open('data.csv', 'r') as f: reader = csv.DictReader(f) rows = list(reader) print(f\"Total rows: {len(rows)}\") for row in rows[:5]: print(row) EOF")
Example 3: Transform and write output file
run_shell(command="python3 << 'EOF' import json with open('input.json') as f: data = json.load(f) transformed = [item.upper() if isinstance(item, str) else item for item in data] with open('output.json', 'w') as f: json.dump(transformed, f, indent=2) print('Transformation complete') EOF")
Limitations
- run_shell executes in the shell environment, not the sandbox - ensure paths and dependencies are available
- Output is limited to stdout/stderr - use file writes for large data
- Complex multi-file projects may require creating temporary script files first