gsheet2md

Original：🇺🇸 English
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Reads Google Sheets and converts content to markdown. Use when the user asks to read, fetch, or convert Google Sheets data to markdown.

2installs
Sourceduongvm57/gsheet2md-skill
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NPX Install

npx skill4agent add duongvm57/gsheet2md-skill gsheet2md

Tags

Translated version includes tags in frontmatter
google-sheetsmarkdown-conversionoauth-credentialsdocument-processingcli-script

SKILL.md Content

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gsheet2md

Read a Google Sheet by 
SPREADSHEET_ID
and turn the result into usable markdown.

Requirements

  • OAuth credentials at 
    ~/.config/google-sheets/oauth-token.json
    with: 
    • client_id
    • client_secret
    • refresh_token
  • Google Sheets API enabled for that OAuth app

Output Policy

  • Use the installed script from the skill directory, but write any authored markdown into 
    ./docs
    of the current workspace.
  • If 
    ./docs
    does not exist, create it before writing files.
  • Do not save generated documents into the installed skill directory.

Usage

Step 1: Resolve the installed script path

Find the directory that contains this 
SKILL.md
. The Python script lives at:
bash
<skill-dir>/scripts/read_sheet.py

Step 2: Fetch sheet data

bash
python3 <skill-dir>/scripts/read_sheet.py --spreadsheet-id <SPREADSHEET_ID> --sheet-name <SHEET_NAME>

Step 3: Convert to readable markdown

After fetching the sheet data, the agent should turn it into a well-structured markdown document.
The agent is responsible for:
  • Understanding the data structure
  • Formatting sections with clear headings, tables, and lists
  • Writing short descriptions where needed
  • Organizing the content for human readers
  • Saving the final markdown file under 
    ./docs/<derived-sheet-name>.md
    in the current workspace

Parameters

ParameterRequiredDescription
--spreadsheet-id
YesThe Google Spreadsheet ID
--sheet-name
NoSheet name to read. Defaults to the first sheet.
--credentials
NoOAuth credentials path. Defaults to 
~/.config/google-sheets/oauth-token.json
.
--output
NoOutput file path. Defaults to stdout.
--format
NoOutput format: 
json
(default), 
table
, or 
text
.
--raw
NoKeep empty columns instead of cleaning them.

Example

bash
# Fetch as JSON
python3 <skill-dir>/scripts/read_sheet.py \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --sheet-name "Sheet1"

# Fetch as markdown table
python3 <skill-dir>/scripts/read_sheet.py \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --format table

# Save raw output directly into the current workspace docs folder
mkdir -p ./docs
python3 <skill-dir>/scripts/read_sheet.py \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --format table \
  --output ./docs/sheet1.md

OAuth Credentials Format

json
{
  "type": "oauth",
  "client_id": "your-client-id.apps.googleusercontent.com",
  "client_secret": "your-client-secret",
  "refresh_token": "your-refresh-token"
}

Workflow For Markdown Output

  1. Run the script to fetch the sheet data.
  2. Inspect the returned structure before formatting it.
  3. Ensure 
    ./docs
    exists in the current workspace. If 
    ./docs
    does not exist, create it.
  4. Write a markdown document that matches the content shape instead of forcing a fixed template.
  5. Save the markdown document under 
    ./docs/
    using a filename derived from the sheet name.