catalog-register

/catalog-register — Data Source Registration

Guides Claude through exploring a data source's structure and registering it in the insight-blueprint catalog via MCP tools.

When to Use

• User wants to register a new data source (CSV file, API endpoint, SQL table)
• User wants to catalog an existing dataset with schema information
• User mentions "データカタログ", "ソース登録", or "register"

When NOT to Use

• Updating an existing source (use update_catalog_entry directly)
• Searching the catalog (use search_catalog directly)
• Managing domain knowledge (future SPEC-3 scope)

Workflow

Step 0: User Confirmation Gate

Before proceeding, confirm with the user:

• Ask: "このソースをカタログに登録しますか？"
• If the user declines, exit gracefully with a brief message and do not proceed
• If the user confirms, continue to Step 1

Step 1: Determine Source Type

Ask the user which type of data source to register:

• CSV — Local file with headers
• API — REST API endpoint (e.g., e-Stat, custom API)
• SQL — Database table (e.g., BigQuery, PostgreSQL)

If $ARGUMENTS is provided, use it as the source type.

Step 2: Explore Data Structure

Follow the appropriate exploration workflow below.

Step 3: Build Registration

Construct the add_catalog_entry call with discovered schema.

Step 4: Register and Confirm

Call add_catalog_entry and show the result to the user.

---

CSV Source Workflow

Step 2a: Read File Headers

1. Ask the user for the CSV file path
2. Read the first 5 rows to discover columns:

   Read the file with limit=5 to see headers and sample data
   

3. For each column, infer:
   • name: Header name
   • type: Infer from sample values (string, integer, float, date, boolean)
   • description: Ask user or infer from column name
   • nullable: Check if any sample values are empty
   • examples: First 2-3 non-empty values

Step 2b: Gather Metadata

Ask the user for:

• source_id: A short slug (e.g., local-survey-2024)
• name: Human-readable name
• description: What this dataset contains