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Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations
---
name: excel-creation-fallback-b023374d1bd3
description: Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations
---
# Excel File Creation Fallback
When `execute_code_sandbox` fails for openpyxl or Excel operations, delegate to `shell_agent` which can autonomously handle dependency and environment issues.
## When to Use
- `execute_code_sandbox` fails with import errors for openpyxl or related libraries
- The sandbox environment lacks required dependencies
- You need to create or modify Excel files with complex requirements
- Repeated sandbox execution failures for file I/O operations
## Steps
### Step 1: Attempt with execute_code_sandbox first
Try creating the Excel file using Python's openpyxl library in the code sandbox:
```python
from openpyxl import Workbook
wb = Workbook()
ws = wb.active
ws.append(['Column1', 'Column2', 'Column3'])
wb.save('output.xlsx')
```
### Step 2: If it fails, switch to shell_agent
Delegate the task to shell_agent with a clear, comprehensive task description:
```
Create an Excel file named 'output.xlsx' with the following structure:
- Sheet 1: Data with columns [Date, Metric, Value]
- Include sample data rows with realistic values
- Apply basic formatting (bold headers, cell borders)
- Add a summary section with totals or averages
- Save the file in the current directory
```
### Step 3: Let shell_agent handle the environment
The shell_agent will:
- Decide whether to use Python or Bash
- Install dependencies if needed (e.g., `pip install openpyxl`)
- Write and execute the code
- Automatically retry and fix errors (up to several rounds)
- Confirm the file was created successfully
## Example Task Descriptions
### Basic Excel file:
```
Create an Excel file named 'sales_report.xlsx' with headers: Date, Product, Quantity, Price, Total. Add 10 sample rows of data and a formula column for Total (Quantity * Price).
```
### Complex Excel with formatting:
```
Create an Excel file with multiple sheets:
- Sheet 'Summary': Key metrics and totals
- Sheet 'Details': Full transaction data with columns [ID, Date, Customer, Amount, Status]
- Apply conditional formatting to highlight amounts over 1000
- Add borders to all cells and bold headers
```
### Tiered pricing structure:
```
Create an Excel file with a tiered pricing table:
- Column A: Quantity thresholds (0, 100, 500, 1000)
- Column B: Unit price at each tier
- Column C: Discount percentage (e.g., 15% discount over 1000 units)
- Include a financial summary section with projections
```
## Why This Pattern Works
`shell_agent` has several advantages over `execute_code_sandbox` for file creation tasks:
| Feature | execute_code_sandbox | shell_agent |
|---------|---------------------|-------------|
| Dependency installation | Manual/preset only | Autonomous |
| Error recovery | Returns error | Auto-retries and fixes |
| Tool selection | Python only | Python, Bash, or other |
| Filesystem access | Sandbox-limited | Full workspace access |
| Verification | None | Can verify file creation |
## Troubleshooting
If shell_agent also struggles:
1. **Be more specific** - Include exact column names, data types, and formatting requirements
2. **Provide sample data** - Include example rows to clarify expected output
3. **Break it down** - For complex files, request creation in stages
4. **Check permissions** - Ensure the target directory is writable
## Alternative Approaches
If shell_agent is unavailable or unsuitable:
- Use `run_shell` with explicit commands (if you know the exact syntax)
- Check for alternative libraries (xlsxwriter, pandas with openpyxl engine)
- Use CSV as intermediate format, then convert to Excel---
name: excel-creation-fallback-b023374d1bd3
description: Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations
---
# Excel File Creation Fallback
When `execute_code_sandbox` fails for openpyxl or Excel operations, delegate to `shell_agent` which can autonomously handle dependency and environment issues.
## When to Use
- `execute_code_sandbox` fails with import errors for openpyxl or related libraries
- The sandbox environment lacks required dependencies
- You need to create or modify Excel files with complex requirements
- Repeated sandbox execution failures for file I/O operations
## Steps
### Step 1: Attempt with execute_code_sandbox first
Try creating the Excel file using Python's openpyxl library in the code sandbox:
```python
from openpyxl import Workbook
wb = Workbook()
ws = wb.active
ws.append(['Column1', 'Column2', 'Column3'])
wb.save('output.xlsx')
```
### Step 2: If it fails, switch to shell_agent
Delegate the task to shell_agent with a clear, comprehensive task description:
```
Create an Excel file named 'output.xlsx' with the following structure:
- Sheet 1: Data with columns [Date, Metric, Value]
- Include sample data rows with realistic values
- Apply basic formatting (bold headers, cell borders)
- Add a summary section with totals or averages
- Save the file in the current directory
```
### Step 3: Let shell_agent handle the environment
The shell_agent will:
- Decide whether to use Python or Bash
- Install dependencies if needed (e.g., `pip install openpyxl`)
- Write and execute the code
- Automatically retry and fix errors (up to several rounds)
- Confirm the file was created successfully
## Example Task Descriptions
### Basic Excel file:
```
Create an Excel file named 'sales_report.xlsx' with headers: Date, Product, Quantity, Price, Total. Add 10 sample rows of data and a formula column for Total (Quantity * Price).
```
### Complex Excel with formatting:
```
Create an Excel file with multiple sheets:
- Sheet 'Summary': Key metrics and totals
- Sheet 'Details': Full transaction data with columns [ID, Date, Customer, Amount, Status]
- Apply conditional formatting to highlight amounts over 1000
- Add borders to all cells and bold headers
```
### Tiered pricing structure:
```
Create an Excel file with a tiered pricing table:
- Column A: Quantity thresholds (0, 100, 500, 1000)
- Column B: Unit price at each tier
- Column C: Discount percentage (e.g., 15% discount over 1000 units)
- Include a financial summary section with projections
```
## Why This Pattern Works
`shell_agent` has several advantages over `execute_code_sandbox` for file creation tasks:
| Feature | execute_code_sandbox | shell_agent |
|---------|---------------------|-------------|
| Dependency installation | Manual/preset only | Autonomous |
| Error recovery | Returns error | Auto-retries and fixes |
| Tool selection | Python only | Python, Bash, or other |
| Filesystem access | Sandbox-limited | Full workspace access |
| Verification | None | Can verify file creation |
## Troubleshooting
If shell_agent also struggles:
1. **Be more specific** - Include exact column names, data types, and formatting requirements
2. **Provide sample data** - Include example rows to clarify expected output
3. **Break it down** - For complex files, request creation in stages
4. **Check permissions** - Ensure the target directory is writable
## Alternative Approaches
If shell_agent is unavailable or unsuitable:
- Use `run_shell` with explicit commands (if you know the exact syntax)
- Check for alternative libraries (xlsxwriter, pandas with openpyxl engine)
- Use CSV as intermediate format, then convert to ExcelImported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.