table-creation

Original：🇺🇸 English

Translated

Create an Extruct company table from user-provided data, upload rows, and optionally add enrichment columns. Handles the full flow: parse input (CSV, pasted list, or structured data), create or reuse a table, upload domains in batches, add agent columns, and trigger enrichment. Triggers on: "create table", "upload companies", "add to extruct", "new extruct table", "import companies", "upload list to extruct".

2installs

Sourceextruct-ai/gtm-skills

Added on2026-03-28

NPX Install

npx skill4agent add extruct-ai/gtm-skills table-creation

SKILL.md Content

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Create Table

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

Extruct API Operations

This skill delegates all Extruct API calls to the

extruct-api

skill.

For all Extruct API operations, read and follow the instructions in

skills/extruct-api/SKILL.md

.

All table creation, row uploads, column creation, and enrichment runs are handled by the extruct-api skill. This skill focuses on parsing input data and orchestrating the flow — the extruct-api skill handles the API execution.

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: Use the extruct-api skill to fetch data from existing table.

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: Delegate to the extruct-api skill to create a company table
Existing table: User provides table ID or URL (
```
https://app.extruct.ai/tables/{id}
```
)

3. Upload rows

Delegate row upload to the extruct-api skill with the parsed domains.

Report progress to the user.

4. Add agent columns (optional)

If the user wants enrichment columns (industry, funding, etc.), delegate column creation to the extruct-api skill.

Column types by use case:

User says	Agent type	Output format	Notes
"add industry"	`llm`	`select` with labels	Classification from profile, no web research needed
"add funding"	`research_pro`	`text`	Needs web research
"classify by vertical"	`llm`	`select` with labels	Classification
"find their tech stack"	`research_pro`	`text`	Needs web research
"score fit 1-5"	`llm` or `research_reasoning`	`grade`	Assessment
"tag multiple categories"	`llm`	`multiselect` with labels	Multiple tags

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

5. Trigger enrichment

Delegate the enrichment run to the extruct-api skill, 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
Column labels: For
```
select
```
/
```
multiselect
```
, collect unique values from user data to build the label list