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excel-creation-fallback

Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.

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Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations

集成工具Excel
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适用场景

  • Continuing Excel creation after a sandbox import error
  • Creating a sales report with formulas and sample data
  • Building multiple sheets with conditional formatting
  • Preparing a tiered pricing table with a financial summary

包含的文件(2)

  • SKILL.md3.6 KB
  • .skill_id37 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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:

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:

Featureexecute_code_sandboxshell_agent
Dependency installationManual/preset onlyAutonomous
Error recoveryReturns errorAuto-retries and fixes
Tool selectionPython onlyPython, Bash, or other
Filesystem accessSandbox-limitedFull workspace access
VerificationNoneCan 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

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