databar-enrichment

Databar Single Enrichment

Run a data enrichment on Databar.ai to look up information about a person, company, email, phone number, or any other entity using 100+ data providers.

Workflow

1. Extract the intent. Identify what the user wants to look up and what entity type it is (person, company, email, phone, domain, etc.).

2. Search for the right enrichment. Call search_enrichments with a descriptive query.

   • For people: try queries like "linkedin profile", "person lookup", "contact info"
   • For companies: "company data", "domain lookup", "technographics"
   • For emails: "email finder", "email verification"
   • For phones: "phone lookup", "mobile number"
   • Use the category filter when helpful: people, company, email, phone, social, financial, verification

3. Inspect the enrichment before running. Call get_enrichment_details with the enrichment_id from step 2. Check:

   • Required parameters — make sure you have all of them from the user's input
   • Price — note the credit cost
   • If you're missing a required parameter, ask the user for it
   • For each param, check type_field and choices:
     • type_field: "select" — the param expects one value from a fixed list
     • type_field: "mselect" — the param expects an array of values from a fixed list

4. Resolve choices for select/mselect params. If a param has a choices object, you must pass a valid id (not the display name).

   • choices.mode = "inline" — valid options are in choices.items[].id. Pick from there directly.
   • choices.mode = "remote" — call get_param_choices({ enrichment_id, param_name }) to fetch valid options. Use q to search if the list is large (e.g. countries, industries). Always pass the id field, not the name.

5. Confirm cost with the user. Tell the user: "This will cost {price} credits using {enrichment_name}. Proceed?" If the user has not confirmed willingness to spend credits, always ask first.