Excel Creation Fallback logo

Excel Creation Fallback

OrganizationPopular
HKUDS
excel-creation-fallback

Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations

Overview

PublisherHKUDS
RepositoryOpenSpace
Skill nameexcel-creation-fallback
Stars
7.7K
Forks
918
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HKUDS on GitHub. Read the source before you install it.

Installation

Install the Excel Creation Fallback AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HKUDS/OpenSpace.git /tmp/OpenSpace
mkdir -p .claude/skills
cp -r /tmp/OpenSpace/benchmarks/gdpval/skills/excel-creation-fallback .claude/skills/excel-creation-fallback
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Excel Creation Fallback in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Excel Creation Fallback on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Excel Creation Fallback is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

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

Frequently asked questions

What does the Excel Creation Fallback AI skill do?

Use shell_agent as fallback when execute_code_sandbox fails for Excel file operations

Why use Excel Creation Fallback on TypingMind?

Because you install it once and use it with any model. Excel Creation Fallback is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Excel Creation Fallback in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/excel-creation-fallback. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Excel Creation Fallback?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Excel Creation Fallback?

As many as you like. As long as a model supports skills, you can use Excel Creation Fallback with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Excel Creation Fallback AI skill free?

Yes. It is published on GitHub by HKUDS under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇