Create Table

End-to-end workflow: parse company data → create/reuse Extruct table → upload rows → add columns → run enrichment.

Environment

Before making API calls, check that EXTRUCT_API_TOKEN is set by running test -n "$EXTRUCT_API_TOKEN" && echo "set" || echo "missing". If missing, ask the user to provide their Extruct API token and set it via export EXTRUCT_API_TOKEN=<value>. Do not proceed until confirmed.

Base URL: https://api.extruct.ai/v1

Official API Reference

• https://www.extruct.ai/docs

Workflow

Step 0: Verify API reference

1. Read local reference: ../list-enrichment/references/api_reference.md
2. Fetch live docs: https://www.extruct.ai/docs
3. Compare endpoints, params, and response fields (especially POST /tables, POST /tables/{id}/rows, POST /tables/{id}/columns)
4. If discrepancies found:
   • Update the local reference file
   • Flag changes to the user before proceeding
5. Proceed with the skill workflow

1. Parse input data

Accept data in any of these formats:

Pasted list (most common): User pastes company names, URLs, and metadata as freeform text. Parse into structured records. Extract domains by stripping protocol, www., and trailing slashes.

CSV file: Read CSV, map columns to find the URL/domain column.

Extruct table URL: Fetch data from existing table via API.

Key rules:

• Skip entries with no URL (e.g., "Stealth" companies)
• Deduplicate by domain
• Ask which metadata fields to preserve (country, stage, industry, etc.)

2. Decide: create new table or add to existing

Ask the user:

• New table: Create via POST /tables
• Existing table: User provides table ID or URL (https://app.extruct.ai/tables/{id})

To create a new company table, use POST /tables with kind: "company" and a single input column (kind: "input", key: "input"). The company kind auto-enriches each domain with Company Profile, Company Name, and Company Website columns.

3. Upload rows in batches

Upload domains via POST /tables/{table_id}/rows in batches of 50. Each row: { "data": { "input": "domain.com" } }. Add 0.5s delay between batches.

Report progress: "Batch 1: uploaded 50 rows OK"

4. Add agent columns (optional)

If the user wants enrichment columns (industry, funding, etc.), add them after upload via POST /tables/{table_id}/columns.

Column types by use case:

See the list-enrichment skill for full column types and output formats.

5. Trigger enrichment

Run via POST /tables/{table_id}/run with { "mode": "new", "columns": [new_column_ids] }, scoped to only the newly added agent columns.

If no agent columns were added, skip this step.

6. Report to user

Provide:

• Table URL: https://app.extruct.ai/tables/{table_id}
• Row count uploaded
• Columns added
• Cells queued for enrichment
• Any rows skipped (stealth, duplicates, invalid URLs)

Input Parsing Patterns

Freeform pasted list (5-line groups)

Company Name
URL (or "Stealth")
Country
Industry
Funding Stage

Parse by splitting into 5-line chunks. Filter where URL == "Stealth".

CSV

Map columns: look for "website", "url", "domain", "Company Website". Extract domain from whichever column contains URLs.

Single-column domain list

example.com
startup.io
company.ai

Direct upload — each line is a domain.

Common Pitfalls

• Domain format: Strip protocol and trailing slash. https://www.example.com/ → example.com
• Stealth companies: Skip — no domain to enrich
• Duplicates: Deduplicate by domain before upload
• Batch limits: Max 50 rows per API call
• Column labels: For select/multiselect, collect unique values from user data to build the label list
• Run timing: Trigger run AFTER all rows and columns are added