google-sheets-automation
Lightweight Google Sheets integration with standalone OAuth authentication. No MCP server required. Full read/write access.
Best use case
google-sheets-automation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Lightweight Google Sheets integration with standalone OAuth authentication. No MCP server required. Full read/write access.
Teams using google-sheets-automation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/google-sheets-automation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How google-sheets-automation Compares
| Feature / Agent | google-sheets-automation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Lightweight Google Sheets integration with standalone OAuth authentication. No MCP server required. Full read/write access.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Google Sheets
Lightweight Google Sheets integration with standalone OAuth authentication. No MCP server required. Full read/write access.
> **Requires Google Workspace account.** Personal Gmail accounts are not supported.
## First-Time Setup
Authenticate with Google (opens browser):
```bash
python scripts/auth.py login
```
Check authentication status:
```bash
python scripts/auth.py status
```
Logout when needed:
```bash
python scripts/auth.py logout
```
## Read Commands
All operations via `scripts/sheets.py`. Auto-authenticates on first use if not logged in.
```bash
# Get spreadsheet content as plain text (default)
python scripts/sheets.py get-text SPREADSHEET_ID
# Get spreadsheet content as CSV
python scripts/sheets.py get-text SPREADSHEET_ID --format csv
# Get spreadsheet content as JSON
python scripts/sheets.py get-text SPREADSHEET_ID --format json
# Get values from a specific range (A1 notation)
python scripts/sheets.py get-range SPREADSHEET_ID "Sheet1!A1:D10"
python scripts/sheets.py get-range SPREADSHEET_ID "A1:C5"
# Find spreadsheets by search query
python scripts/sheets.py find "budget 2024"
python scripts/sheets.py find "sales report" --limit 5
# Get spreadsheet metadata (sheets, dimensions, etc.)
python scripts/sheets.py get-metadata SPREADSHEET_ID
```
## Write Commands
```bash
# Update a range of cells with values (JSON 2D array)
python scripts/sheets.py update-range SPREADSHEET_ID "Sheet1!A1:B2" '[["Hello","World"],["Foo","Bar"]]'
# Update with RAW input (no formula parsing, treats everything as literal text)
python scripts/sheets.py update-range SPREADSHEET_ID "Sheet1!A1:B1" '[["=SUM(A1:A5)","text"]]' --raw
# Append rows after the last data row
python scripts/sheets.py append-rows SPREADSHEET_ID "Sheet1!A:Z" '[["New Row Col A","New Row Col B"]]'
# Clear values from a range (keeps formatting)
python scripts/sheets.py clear-range SPREADSHEET_ID "Sheet1!A1:B10"
# Batch update (advanced - for formatting, merging, etc.)
python scripts/sheets.py batch-update SPREADSHEET_ID '[{"updateCells":{"range":{"sheetId":0},"fields":"userEnteredValue"}}]'
```
## Spreadsheet ID
You can use either:
- The spreadsheet ID: `1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms`
- The full URL: `https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit`
The script automatically extracts the ID from URLs.
## Output Formats
### Text (default)
Human-readable format with pipe separators:
```
Spreadsheet Title: Sales Data
Sheet Name: Q1
Name | Revenue | Units
Product A | 10000 | 50
Product B | 15000 | 75
```
### CSV
Standard CSV format, suitable for further processing:
```
Name,Revenue,Units
Product A,10000,50
Product B,15000,75
```
### JSON
Structured data format:
```json
{
"Q1": [
["Name", "Revenue", "Units"],
["Product A", "10000", "50"]
]
}
```
## A1 Notation Examples
- `Sheet1!A1:B10` - Range A1 to B10 on Sheet1
- `Sheet1!A:A` - All of column A on Sheet1
- `Sheet1!1:1` - All of row 1 on Sheet1
- `A1:C5` - Range on the first sheet
## Value Input Options
- **USER_ENTERED** (default): Values are parsed as if typed by a user. Numbers, dates, and formulas are interpreted.
- **RAW** (`--raw` flag): Values are stored exactly as provided. No parsing of formulas or number formatting.
## Token Management
Tokens stored securely using the system keyring:
- **macOS**: Keychain
- **Windows**: Windows Credential Locker
- **Linux**: Secret Service API (GNOME Keyring, KDE Wallet, etc.)
Service name: `google-sheets-skill-oauth`
Tokens automatically refresh when expired using Google's cloud function.
## When to Use
Use this skill when tackling tasks related to its primary domain or functionality as described above.
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.Related Skills
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