Use Crustdata in Deepline

Human guide: work with your agent → Inspect one Crustdata action before starting provider-backed work. Your first result is a verified input and output contract.

Provider-specific requirements

Use CrustData for structured discovery and enrichment with recall-first filtering.

Start with free autocomplete (crustdata_v3_company_search_autocomplete, crustdata_v3_person_search_autocomplete) to discover canonical values. Confirm these hints with deepline describe <tool-id>.
Preserve recall-first matching: in historical CompanyDB filters, fuzzy (.) was the default and strict [.] was only for an explicit substring request. V3 uses contains. confirm its semantics and current field vocabulary rather than forwarding old operators.
Use crustdata_v3_company_search as the resolver step. for crustdata_v3_company_enrich, prefer domain-based inputs instead of name-only payloads. Check each input schema before converting older company filters.
For job data, use crustdata_v3_job_search for indexed listings or crustdata_v2_live_job_search when freshness is required for a known CrustData company id. Legacy job-listing compatibility actions are hidden from discovery and should not be selected for new workflows.
In changed-company email recovery, use Crust as the second step after LeadMagic and before PDL.
Keep filters composable and inspect a small sample before adding expensive enrichments.
If Crust misses in the first 10 rows for a batch, move it later for the rest of that batch.

Historical CompanyDB / PersonDB filter knowledge

Keep this vocabulary when interpreting existing payloads and results. It is not a V3 input template. New V3 searches take a filters group with op and conditions, whose leaves use field, type, and value. Discover the current field paths and operators with deepline describe <tool-id> before translating. Do not blindly rename tools while keeping these older filters. filters accepts an array of condition objects (AND-combined automatically). Each condition: {"filter_type":"<field>","type":"<operator>","value":"<val>"} or {"filter_name":"<field>","type":"<operator>","value":"<val>"}. filter_name is syntactic sugar for filter_type. human-friendly aliases (e.g. company_investors → crunchbase_investors, company_funding_stage → last_funding_round_type) are auto-mapped. A single condition object (not in array) also works. Company filter_type values: company_name, company_website_domain, linkedin_industries, hq_country, hq_location, region, year_founded, employee_metrics.latest_count, employee_count_range, employee_metrics.growth_6m_percent, employee_metrics.growth_12m_percent, employee_metrics.growth_12m, follower_metrics.latest_count, follower_metrics.growth_6m_percent, crunchbase_investors, tracxn_investors, crunchbase_categories, crunchbase_total_investment_usd, last_funding_date, last_funding_round_type, estimated_revenue_lower_bound_usd, estimated_revenue_higher_bound_usd, linkedin_id, linkedin_profile_url, company_type, acquisition_status, ipo_date, largest_headcount_country, markets, competitor_ids, competitor_websites. Person filter_type values: current_employers.company_website_domain, current_employers.title, current_employers.seniority_level, headline, region, num_of_connections, years_of_experience_raw. Operators: (.) = fuzzy contains (default), [.] = substring, =, !=, in, not_in, >, <, =>, =<. Person search also supports geo_distance for region. Range filtering: There is NO range operator like [100..500] or between. To filter a numeric range, use TWO separate filter conditions with > and < (or => and =<):

[
  {
    "filter_type": "employee_metrics.latest_count",
    "type": ">",
    "value": "100"
  },
  {
    "filter_type": "employee_metrics.latest_count",
    "type": "<",
    "value": "500"
  }
]

Headcount filtering: For headcount, prefer employee_count_range (string enum like "51-200", "201-500") with the in operator when exact buckets work. Use employee_metrics.latest_count with > / < only when you need precise numeric boundaries. Note: employee_metrics.latest_count is valid for sorts and filters, but employee_count_range uses string enum values.

Examples

deepline tools execute crustdata_v3_company_search_autocomplete --input '{"field":"taxonomy.professional_network_industry","query":"software","limit":5}'

Historical search payload for interpreting existing CompanyDB work (not a V3 execution example). It combines recall-first software-industry matching with an exact US HQ filter. Resolve current V3 field/value equivalents through discovery:

{
  "filters": [
    {
      "filter_type": "linkedin_industries",
      "type": "(.)",
      "value": "software"
    },
    { "filter_type": "hq_country", "type": "=", "value": "USA" }
  ],
  "limit": 5
}

For CSV company-name lookup, use a supplied Play if it fits. Otherwise discover with deepline plays search company and inspect the selected contract with deepline describe <play-ref>. Confirm the tool hint below with deepline describe crustdata_v3_company_search_autocomplete. autocomplete does not replace the company-search resolver or the domain-first enrichment policy. Save this custom workflow as company-lookup.play.ts:

import { definePlay } from 'deepline';

export default definePlay(
  'company-lookup',
  async (ctx, input: { csv: string }) => {
    const accounts = await ctx.csv(input.csv, { required: ['Company'] });
    const rows = await ctx
      .dataset('accounts', accounts)
      .withColumn('company_lookup', (row, rowCtx) =>
        rowCtx.tools.execute({
          id: 'company_lookup',
          tool: 'crustdata_v3_company_search_autocomplete',
          input: { field: 'basic_info.name', query: row.Company, limit: 1 },
          description: 'Look up the canonical company-name candidate.',
        }),
      )
      .run({});
    return { rows };
  },
  { description: 'Look up company names from the supplied accounts CSV.' },
);

deepline plays check company-lookup.play.ts
deepline plays run --file company-lookup.play.ts --csv accounts.csv --watch

V3’s basic_info.name replaces the historical autocomplete field company_name. the query still comes from Company and limit remains 1. Autocomplete declares no semantic getters, so retain its full tool response as evidence instead of inventing an extractedValues accessor. Keep the input columns and lookup evidence. For larger or uncertain authorized work, inspect a small representative input before scaling. do not add pilot runs or repeat approval for a small supplied Play. Use deepline runs get <run-id> and its full-result/export commands to retrieve existing rows into accounts.csv.out.csv. A request to inspect results does not authorize another run, paid fallback, or repair.

Find an applicable action

Confirm your effective workspace, then search the live catalog:

deepline auth status --json
deepline search "Crustdata" --type tools --json

Search returns candidates. Check the returned provider and operation rather than selecting a similar title automatically.

Inspect the selected contract

Replace <returned-tool-id> with the identifier returned by discovery:

deepline describe <returned-tool-id> --json

These commands do not execute the selected provider action. Read its required inputs, supported access mode, pricing unit, outputs, and limits. A connection does not establish that every action supports BYOK. Follow the provider-specific requirements above and the live action contract.

Prepare one reviewed input

Use one authorized record that matches the inspected schema. Preserve its source identity and define the result you will accept. Open the action reference for its payload and response shape. Provider-backed execution can incur usage or external effects. For reusable logic, follow Write Plays. For direct-call recovery, use Tool execution recovery.

Continue only when the workspace, provider, required fields, acceptance rule, and applicable price are understood. Keep unavailable access separate from no-result evidence.

​Provider-specific requirements

​Historical CompanyDB / PersonDB filter knowledge

​Examples

​Find an applicable action

​Inspect the selected contract

​Prepare one reviewed input

Provider-specific requirements

Historical CompanyDB / PersonDB filter knowledge

Examples

Find an applicable action

Inspect the selected contract

Prepare one reviewed input