| name | code-execution-fallback |
| description | Handle code execution failures with fallback strategies and anchored workspace paths |
Code Execution Fallback & Workspace Anchoring
This skill provides a robust pattern for executing code when the primary method fails, combined with proper workspace path management to prevent file location errors.
Core Techniques
1. Workspace Path Anchoring
Always establish and verify your working directory at the start of any task:
import os
workspace_path = os.getcwd()
print(f"Working directory: {workspace_path}")
pwd
echo "Current directory: $(pwd)"
Why: Prevents files from being written to unexpected locations when agents switch between tools.
2. Execution Fallback Ladder
When execute_code_sandbox fails, follow this escalation pattern:
Level 1: Retry with Simpler Code
- Simplify the code structure
- Remove complex dependencies
- Add explicit error handling
Level 2: Use run_shell with Heredoc
When sandbox execution repeatedly fails, switch to shell execution:
python3 << 'EOF'
import os
import pandas as pd
data = {"col1": [1, 2, 3], "col2": ["a", "b", "c"]}
df = pd.DataFrame(data)
df.to_csv("output.csv", index=False)
print("File written successfully")
EOF
Key points:
- Use
<< 'EOF' (quoted) to prevent variable expansion
- Include all imports and dependencies inline
- Add explicit success/failure messages
Level 3: Delegate to shell_agent
For complex multi-step tasks with error recovery needs:
Task: Create a data processing pipeline that reads CSV, transforms data, and outputs Excel
Requirements:
- Handle missing values
- Apply transformations
- Write to ./output/ directory
- Retry on transient errors
3. Explicit Path Management
Always use absolute or explicitly relative paths:
df.to_csv("output/data.csv")
import os
base_path = os.getcwd()
output_dir = os.path.join(base_path, "output")
os.makedirs(output_dir, exist_ok=True)
df.to_csv(os.path.join(output_dir, "data.csv"))
cd some_dir && python script.py
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
cd "$SCRIPT_DIR"
python script.py
Decision Tree
execute_code_sandbox fails?
├── Yes, with syntax/import errors → Fix code, retry Level 1
├── Yes, with timeout/resource errors → Use Level 2 (run_shell heredoc)
├── Yes, with unknown/unclear errors → Use Level 3 (shell_agent)
└── No, success → Verify output file exists at expected path
Common Failure Scenarios & Solutions
| Error Type | Likely Cause | Recommended Fallback |
|---|
| ModuleNotFoundError | Missing packages | run_shell with pip install first |
| Timeout | Long-running operation | shell_agent with progress tracking |
| PermissionError | Wrong directory | Verify workspace path, use explicit paths |
| Unknown error | Sandbox limitations | run_shell or shell_agent |
Example: Robust File Generation
import os
workspace = os.getcwd()
print(f"Workspace: {workspace}")
output_path = os.path.join(workspace, "deliverables")
os.makedirs(output_path, exist_ok=True)
try:
with open(os.path.join(output_path, "report.txt"), "w") as f:
f.write("Content here")
print(f"Success: File written to {output_path}")
except Exception as e:
print(f"Error: {e}")
raise
Anti-Patterns to Avoid
- ❌ Assuming current directory without verification
- ❌ Using relative paths like
../output/file.txt without context
- ❌ Repeatedly retrying failed
execute_code_sandbox without changing approach
- ❌ Not checking if output files exist after generation
- ❌ Mixing implicit and explicit path styles in same task
Verification Checklist
After any code execution: