sanjay3290/postgres-skill/google-sheets

Claude Code and agent skill by sanjay3290/postgres-skill

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Read and write Google Sheets spreadsheets - get content, update cells, append rows, fetch specific ranges, search for spreadsheets, and view metadata. Use when user asks to: read a spreadsheet, update cells, add data to Google Sheets, find a spreadsheet, check sheet contents, export spreadsheet data, or get cell values. Lightweight integration with standalone OAuth authentication supporting full read/write access.

Install

npx vskill@latest install sanjay3290/postgres-skill/google-sheets

SKILL.md

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.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

See the full security report

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

See evaluation results

Source

Popularity

Repository stars
240
Repository forks
21
7-day trend score
27

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 1 May 2026, 6 months ago.

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