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Google Sheets

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win4r
google_sheets

Read, write, and manage the user's Google Sheets.

Overview

Publisherwin4r
RepositoryMuseAI-Skills
Skill namegoogle_sheets
Stars
382
Forks
116
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by win4r on GitHub. Read the source before you install it.

Installation

Install the Google Sheets 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.
    https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/google-sheets
  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/win4r/MuseAI-Skills.git /tmp/MuseAI-Skills
mkdir -p .claude/skills
cp -r /tmp/MuseAI-Skills/opt/hatch/skills/google-sheets .claude/skills/google_sheets
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Sheets 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 Google Sheets 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 Google Sheets 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.

Google Sheets

Purpose

Manage Google Sheets through hatch_gws_cli; the vendored Google Workspace CLI is the only implementation path.

Tooling

Use exec to run:

sh
hatch_gws_cli sheets <resource> <method> [flags]

Connection management

sh
hatch_gws_cli sheets status
hatch_gws_cli sheets disconnect

Sheets operations

Core patterns:

  • hatch_gws_cli sheets status
  • hatch_gws_cli sheets disconnect
  • hatch_gws_cli schema sheets.spreadsheets.get
  • hatch_gws_cli schema sheets.spreadsheets.create
  • hatch_gws_cli schema sheets.spreadsheets.values.get
  • hatch_gws_cli schema sheets.spreadsheets.values.append
  • hatch_gws_cli schema sheets.spreadsheets.batchUpdate

Common raw API calls:

  • hatch_gws_cli sheets spreadsheets get --params '{"spreadsheetId":"<spreadsheet_id>"}'
  • hatch_gws_cli sheets spreadsheets create --json '{"properties":{"title":"My Spreadsheet"}}'
  • hatch_gws_cli sheets spreadsheets values get --params '{"spreadsheetId":"<spreadsheet_id>","range":"Sheet1!A1:D10"}'
  • hatch_gws_cli sheets spreadsheets values append --params '{"spreadsheetId":"<spreadsheet_id>","range":"Sheet1!A:D","valueInputOption":"USER_ENTERED"}' --json '{"values":[["a","b"],["c","d"]]}'
  • hatch_gws_cli sheets spreadsheets batchUpdate --params '{"spreadsheetId":"<spreadsheet_id>"}' --json '{"requests":[{"addSheet":{"properties":{"title":"Q2"}}}]}'

Vendored helpers are also available:

  • hatch_gws_cli sheets +read ...
  • hatch_gws_cli sheets +append ...

JSON output contract:

  • status: parse status, connect_url, and disconnect_url
  • disconnect: parse ok, action, status, and disconnect_url

Formatting spreadsheet content

Write and format the spreadsheet through the Sheets API. Do not upload a file over it.

  1. Write the values with spreadsheets.create, values.update, or values.append. Set valueInputOption to USER_ENTERED so Sheets parses dates, currency, and formulas.
  2. Set the styling in one spreadsheets.batchUpdate call. repeatCell with userEnteredFormat sets the header style and the number formats. updateSheetProperties freezes the header row. updateDimensionProperties sets column widths. A new spreadsheet can carry these formats in the spreadsheets.create body instead.
  3. Read the result back before you call it ready. A successful write proves the API accepted the request, not that the sheet reads correctly. spreadsheets.get returns no cell data by default, so pass a field mask: hatch_gws_cli sheets spreadsheets get --params '{"spreadsheetId":"<spreadsheet_id>","ranges":"<tab>!A1:F10","fields":"sheets(properties(title,gridProperties(frozenRowCount)),data(rowData(values(formattedValue,effectiveFormat(backgroundColor,numberFormat,textFormat)))))"}'
  4. Never publish a .xlsx file over a spreadsheet with drive files update. Google replaces the full contents of the file, so that upload discards every other tab and every edit the user made. To change one part of a spreadsheet, use values.update or spreadsheets.batchUpdate. To give the user a workbook to download, build a spreadsheet artifact and attach the file.

Auth

Authentication is handled by the wrapper's status and disconnect subcommands. Do not hand-write credential files or run raw gws auth ....

First-use setup flow

  1. Run hatch_gws_cli sheets status.
  2. If status is unavailable, tell the user that Google Sheets is not available on this device. Do not offer alternative integration approaches or ask the user for credentials.
  3. If status is not_connected and connect_url is present, replace <connect_url> with the returned URL and share exactly this Markdown link: [Connect Google Sheets](<connect_url>); do not paste the raw URL separately. Wait for the user to reconnect.
  4. Once status is connected, proceed with Sheets operations.

Operating Rules

  1. Use schema before unfamiliar Sheets methods so --params and --json match the current vendored CLI contract.
  2. Use A1 notation for ranges unless the user explicitly wants a different API path.
  3. Creating a spreadsheet, clearing cells, and editing a spreadsheet owned only by the user may proceed from a clear request. Confirm before editing a shared spreadsheet because its contents can be exposed to or changed for other people.
  4. Treat spreadsheet IDs and sheet IDs as opaque strings and only use IDs returned by prior commands or explicit user input.
  5. Run hatch_gws_cli sheets disconnect. After running it, when disconnect_url is present, replace <disconnect_url> with the returned URL and share exactly this Markdown link: [Disconnect Google Sheets](<disconnect_url>); do not paste the raw URL separately.
  6. Prefer spreadsheets.get or sheets +read before writing when you need to inspect current sheet structure or cell contents. To write or style a sheet, follow "Formatting spreadsheet content" above.
  7. After a read or write action, confirm the user-visible result only. Do not surface raw API identifiers (spreadsheet and sheet IDs) or other internal response fields (page tokens/cursors, raw JSON) in text shown to the user unless the user asks for them or you need them to troubleshoot a failure; keep using them internally to chain follow-up commands.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Google Sheets AI skill do?

Read, write, and manage the user's Google Sheets.

Why use Google Sheets on TypingMind?

Because you install it once and use it with any model. Google Sheets 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 Google Sheets in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/google-sheets. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Google Sheets?

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 Google Sheets?

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

Is the Google Sheets AI skill free?

It is published on GitHub by win4r. Check the repository for licensing terms. 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.

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