Google Sheets Automation

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):

python scripts/auth.py login

Check authentication status:

python scripts/auth.py status

Logout when needed:

python scripts/auth.py logout

Read Commands

All operations via scripts/sheets.py. Auto-authenticates on first use if not logged in.

# 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

# 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:

{
  "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.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Google Sheets Automation"

Storing Results

After completing work, store workflow/automation decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags google-sheets-automation workflow

Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>

Playbook Engine

Combine this skill with others using the Playbook Engine (execution/workflow_engine.py) for guided multi-step automation with progress tracking.