extruct-api

# Extruct API Use `<extruct_api_cli>` for supported Extruct operations. Do not construct raw HTTP requests for operations the CLI already supports. Extruct AI is a company discovery and research platform for finding, enriching, and evaluating companies. Its core workflows are semantic search, lookalike search, and Deep Search for company discovery, plus AI Tables for repeatable company and people enrichment, scoring, and contact-finding workflows. ## Source Of Truth Use the bundled CLI and the instructions in this skill as the default path. When behavior is unclear, when the user asks for a capability that may not be covered here, or when the request may depend on recently changed API behavior, consult the official Extruct API reference as the source of truth: - https://www.extruct.ai/docs/api-reference/introduction Decision rule: - if the CLI already supports the operation, use the CLI - if the CLI does not cover the operation or the documented behavior here conflicts with the live API, defer to the official API docs ## Resolve The Bundled CLI First `<extruct_api_cli>` means the absolute path to the bundled CLI script for this skill. - Resolve it from the directory that contains this `SKILL.md`. - In shell or Bash tool calls, prefer the resolved absolute path, not `scripts/extruct-api` relative to the workspace root. - All command examples below use `<extruct_api_cli>` as shorthand for that resolved absolute path. Example: ```bash /absolute/path/to/skills/extruct-api/scripts/extruct-api auth user ``` ## Core Workflow This section covers the default operating intent of the skill: identify the Extruct object the user is working with, choose the right execution path, inspect before mutating, and use the CLI to carry the task through to completion. 1. Resolve `<extruct_api_cli>` first, then establish API access. Before the first authenticated CLI call in a conversation, run `<extruct_api_cli> auth user`. If it fails, run `<extruct_api_cli> healthcheck` to distinguish credential problems from connectivity issues. 2. Classify the request into the right Extruct path: - if the user provides an Extruct table URL or a raw table UUID, treat it as an existing table operation first - if the user provides an Extruct task URL or a raw task UUID, treat it as an existing Deep Search task first - company discovery: semantic search, lookalike search, or Deep Search - existing table operation: inspect, add/update rows or columns, run, poll, read - company-table workflow: enrich or score companies in a reusable table - people workflow: find people at companies or enrich existing people rows 3. If the user already has a table or task, inspect it before mutating it. Default inspection is `tables get`, `columns list`, and a small `tables data` page. When you only need a surgical read, add `--columns` on the first `tables data` call instead of fetching the full row payload. 4. Start from the inline command and payload examples in this file. If a payload spans more than a few lines, prefer `--payload-file`. Read `references/column-guide.md` before designing or changing columns. 5. Carry async work through to completion with `tables poll` or `deep-search poll`, then summarize the final result or API error in plain language, including IDs, counts, and the next relevant object when it matters. If any request shape, field name, response contract, or endpoint capability is uncertain while executing this workflow, re-check the official API reference before proceeding: - https://www.extruct.ai/docs/api-reference/introduction ## Resolve Extruct Identifiers Users may provide Extruct objects as raw IDs or as dashboard URLs. Interpret them as follows: - if the user provides an Extruct table URL such as `https://app.extruct.ai/tables/<table_id>` or `http://app.extruct.ai/tables/<table_id>`, treat the path segment after `/tables/` as the table id - if the user provides an Extruct task URL such as `https://app.extruct.ai/tasks/<task_id>` or `http://app.extruct.ai/tasks/<task_id>`, treat the path segment after `/tasks/` as the Deep Search task id - if the URL includes extra path segments, query params, or fragments, still extract the id from the `/tables/<table_id>` or `/tasks/<task_id>` segment - if the user provides a raw table UUID, use it directly as the table id - if the user provides a raw task UUID, use it directly as the task id - do not ask the user to restate an id that is already present in the URL - when a table URL is present, default to the existing-table workflow unless the user explicitly asks for a new table or a search workflow - when a task URL is present, default to the Deep Search task workflow unless the user explicitly asks to start a new search task Example: User request: ```text Add a funding column to http://app.extruct.ai/tables/0a1a669a-9a40-497c-bb00-d49dd8ee5b74 ``` Resulting table id: ```text 0a1a669a-9a40-497c-bb00-d49dd8ee5b74 ``` First CLI reads: ```bash <extruct_api_cli> tables get 0a1a669a-9a40-497c-bb00-d49dd8ee5b74 <extruct_api_cli> columns list 0a1a669a-9a40-497c-bb00-d49dd8ee5b74 <extruct_api_cli> tables data 0a1a669a-9a40-497c-bb00-d49dd8ee5b74 --limit 20 --offset 0 ``` User request: ```text Check results for https://app.extruct.ai/tasks/d530c3ad-626c-4d7b-ab15-181d4058e4f8 ``` Resulting task id: ```text d530c3ad-626c-4d7b-ab15-181d4058e4f8 ``` First CLI reads: ```bash <extruct_api_cli> deep-search get d530c3ad-626c-4d7b-ab15-181d4058e4f8 <extruct_api_cli> deep-search results d530c3ad-626c-4d7b-ab15-181d4058e4f8 --limit 20 --offset 0 ``` ## Choose The Right Company-Finding Path ### Semantic Search Use semantic search when the user describes a market, ICP, category, product, or use case in natural language. Typical asks: - "search Extruct for AI procurement startups" - "find German fintech companies in Extruct" - "show me B2B treasury automation companies" Commands: ```bash <extruct_api_cli> companies search --query "vertical SaaS for logistics procurement" --limit 20 <extruct_api_cli> companies search --query "enterprise sales AI" \ --filters '{"include":{"country":["United States"]},"range":{"founded":{"min":2018}}}' \ --offset 20 --limit 20 ``` Use `--filters` when the user specifies geography, city, company size, or founded range. Pass a JSON object like one of these as the `--filters` value. ```json { "include": { "country": ["United States"], "size": ["51-200", "201-500"] } } ``` ```json { "range": { "founded": { "min": 2018, "max": 2024 } } } ``` If search filters or pagination behavior appear different from the guidance here, verify current request and response details in the official API reference before guessing. ### Lookalike Search Use lookalike search when the user already has a reference company and wants similar companies. Prefer domains or URLs for `--company-identifier` unless a prior Extruct response already gives you a UUID. Typical asks: - "find companies similar to Stripe in Extruct" - "lookalike search from ramp.com" Commands: ```bash <extruct_api_cli> companies similar --company-identifier extruct.ai --limit 20 <extruct_api_cli> companies similar --company-identifier stripe.com \ --filters '{"include":{"country":["United Kingdom"]}}' ``` Pagination uses the same `--offset` and `--limit` behavior as semantic search. If identifier handling is unclear for a specific seed company or the live API behavior differs, verify the current lookalike-search request contract in the official API reference. ### Deep Search Use Deep Search when the user wants a higher-precision asynchronous company search, wants explicit criteria, or is comfortable waiting for a task. Typical asks: - "run Deep Search for B2B revenue intelligence vendors" - "find high-conviction AI procurement startups and show me the first result" Create a task: ```bash <extruct_api_cli> deep-search create --payload '{"query":"AI procurement startups serving enterprise finance teams","desired_num_results":25}' ``` Create a task with explicit criteria: ```bash <extruct_api_cli> deep-search create --payload-file criteria.json ``` `criteria.json`: ```json { "query": "vertical SaaS companies serving freight forwarding", "desired_num_results": 25, "criteria": [ { "key": "has_logistics_focus", "name": "Logistics Focus", "criterion": "Company serves freight forwarding or logistics operations." }, { "key": "b2b_fit", "name": "B2B Fit", "criterion": "Company sells primarily to business buyers." } ] } ``` Inspect, poll, read results, or request more: ```bash <extruct_api_cli> deep-search list --limit 20 <extruct_api_cli> deep-search get <task_id> <extruct_api_cli> deep-search poll <task_id> <extruct_api_cli> deep-search results <task_id> --limit 20 --offset 0 <extruct_api_cli> deep-search resume <task_id> --payload '{"desired_new_results":25}' ``` Deep Search notes: - `deep-search results` can be read while the task is still running - `deep-search poll` completes when `status == "done"` or `is_exhausted == true` - if the user wants follow-on enrichment, move shortlisted domains into a company table - if the payload spans more than a few lines or includes `criteria`, prefer `--payload-file` over inline `--payload` If Deep Search payload fields, task states, or resume behavior are unclear, verify them against the official API reference before constructing raw fallback requests. Read `references/finding-companies.md` when the task is a fuller company-discovery workflow instead of a single search command. ## Operate Existing Tables Use these commands when the user already has a table and wants to inspect it, change rows or columns, run new work, or read results. Typical asks: - "add a funding column to this Extruct table" - "poll this Extruct table until it finishes" - "show me the first 20 rows from this table" - "rerun only the new columns on this table" If table payload shape, row schema, or run behavior is unclear, check the official API reference before mutating live tables: - https://www.extruct.ai/docs/api-reference/introduction ### Create A Table Use this when the user needs a new table before doing anything else. ```bash <extruct_api_cli> tables create --payload '{ "name":"Target Accounts", "kind":"company" }' ``` ### Inspect Before Mutating If the user supplied a table URL, extract the table id first and use that id for all CLI commands below. ```bash <extruct_api_cli> tables list --limit 20 <extruct_api_cli> tables get <table_id> <extruct_api_cli> columns list <table_id> <extruct_api_cli> tables data <table_id> --limit 20 --offset 0 <extruct_api_cli> tables data <table_id> --limit 20 --offset 0 --columns company_name,company_website <extruct_api_cli> rows get <table_id> <row_id> ``` ### Update, Clone, Or Delete A Table Update metadata: ```bash <extruct_api_cli> tables update <table_id> --payload '{ "name":"Target Accounts - Updated", "description":"High-priority accounts for enrichment" }' ``` Clone or delete: ```bash <extruct_api_cli> tables clone <table_id> --schema-only <extruct_api_cli> tables delete <table_id> --yes ``` `--schema-only` clones the columns and structure without copying row data. Without `--schema-only`, clone copies both schema and rows. ### Add, Update, Or Delete Rows Use company domains or URLs as the safest `input` on company tables. Default to `"run": false` while iterating so you can inspect rows and columns before spending more work. Only switch to `"run": true` when the user explicitly wants add-and-run in one step. Before deleting, inspect either the specific row with `rows get` or a small `tables data` page so you only remove the intended records. Create rows: ```bash <extruct_api_cli> rows create <table_id> --payload '{ "rows":[ {"data":{"input":"extruct.ai"}}, {"data":{"input":"stripe.com"}} ], "run":false }' ``` Update rows: ```bash <extruct_api_cli> rows update <table_id> --payload '{ "rows":[ { "id":"<row_id>", "data":{"input":"https://extruct.ai"} } ], "run":false }' ``` Delete rows: ```bash <extruct_api_cli> rows delete <table_id> --yes --payload '{ "rows":[ "<row_id_1>", "<row_id_2>" ] }' ``` Row-deletion notes: - deletion is bulk and row-ID based - `rows delete` requires `--yes` - a successful response returns the deleted row IDs ### Add, Update, Or Delete Columns Read `references/column-guide.md` before designing or changing columns. Prefer built-in column kinds before custom prompts. If a column kind, payload field, or validation rule in this skill looks stale, verify the current table and column contract in the official API reference before retrying. Add a simple research column: ```bash <extruct_api_cli> columns add <table_id> --payload '{ "column_configs":[ { "kind":"agent", "name":"Latest Funding", "key":"latest_funding", "value":{ "agent_type":"research_pro", "prompt":"What is the latest funding round for the company? Return round type, amount, date, and lead investors when available.", "output_format":"text" } } ] }' ``` Update a column: ```bash <extruct_api_cli> columns update <table_id> <column_id> --payload '{ "kind":"agent", "name":"Latest Funding", "key":"latest_funding", "value":{ "agent_type":"research_pro", "prompt":"What is the latest funding round for the company? Return round type, amount, date, and lead investors when available.", "output_format":"text" } }' ``` Delete a column: ```bash <extruct_api_cli> columns delete <table_id> <column_id> --yes ``` ### Run And Poll Default incremental run: ```bash <extruct_api_cli> tables run <table_id> <extruct_api_cli> tables run <table_id> --payload '{ "mode":"new", "columns":["<column_id_1>","<column_id_2>"] }' ``` Poll and then read a small result page: ```bash <extruct_api_cli> tables poll <table_id> <extruct_api_cli> tables data <table_id> --limit 20 --offset 0 <extruct_api_cli> tables data <table_id> --limit 20 --offset 0 --columns company_name,latest_funding ``` Table-operation defaults: - prefer `mode: "new"` when iterating on an existing table