Discover

by hunter-io44f0f5689d2dNo licenseListed Oct 8, 2026Updated Oct 8, 2026

Finds companies matching criteria (industry, size, location, technologies), estimates how many contacts exist across them, and manages saved searches. Use when the user wants to find companies, build a target-account list, or size a prospecting batch before spending credits. Browsing is free.

Instructions onlyMarketing & Sales
AI-generated overview

Finds companies matching criteria, sizes how many contacts they hold, and manages saved searches.

What it does
Takes a natural-language query and returns matching companies with domain, industry, size and location, presented as a table with suggested next actions. It can also report how many email addresses exist across a set of companies to help size a prospecting batch, and it lists, loads, creates or deletes saved searches. Company discovery and contact counts are free; pulling actual contacts is handled by other skills and consumes credits.
When to use it
Use it when the user wants to find companies, build a target-account list, or estimate how many contacts a set of companies holds before spending credits. It is also used to save, rerun or delete a saved search.
Requirements
Requires access to the Hunter API tools named in the document (Find-Companies, Find-People, List-Saved-Searches, Get-Saved-Search, Create-Saved-Search, Delete-Saved-Search) and network access to them. No scripts ship with the skill; it is instructions only.

Discover

Find companies matching any criteria and size how many contacts they hold — all free, no credits consumed. To turn companies into named, verified contacts you then use Domain Search (which consumes credits); for the full "find people by role" pipeline, use the prospecting skill.

Examples

  • /hunter:discover fintech startups in France
  • /hunter:discover SaaS companies using Salesforce
  • "Find healthcare companies in Germany with 100+ employees"
  • "How many contacts could I get across these fintech companies?"
  • "Series B startups in Europe"
  • "Save this search as 'French fintech'"
  • "Run my saved search"

Steps

  1. Find companies. Pass the user's query directly to Find-Companies as the query parameter — it accepts natural language and handles parsing.

  2. Present the results:

# Discover: Fintech Startups in France
**Found:** 43 companies | **Showing:** 10
| Company | Domain | Industry | Size | Location ||---------|--------|----------|------|----------|| Qonto | qonto.com | Fintech | 150 | Paris, FR || Pennylane | pennylane.com | Fintech | 120 | Paris, FR || Swan | swan.io | Fintech | 95 | Paris, FR || ... | ... | ... | ... | ... |
## Next Actions1. Narrow or refine the criteria to surface different results (Find-Companies / Find-People have no offset paging)2. Find the actual contacts at one of these (Domain-Search — consumes credits)3. Estimate how many contacts these companies hold, free (see "Sizing a batch" below)4. Save companies to a list (company-lists skill)5. Run the full people pipeline on these (prospecting skill)6. Rerun one of your saved searches (List-Saved-Searches)
  1. If results are too broad (hundreds of companies), suggest narrowing: "That's a broad search. Try adding filters like industry, size, location, or technology."

  2. If zero results, suggest loosening criteria: "No companies matched. Try broadening — for example, widen the location or employee range."

  3. Remind users this is free: "Discovering companies is free — refine as many times as you'd like. You only spend credits when you pull the actual contacts with Domain Search."

Finding people by role

Find-People does not return individual people — it reports, for each matching company, how many email addresses Hunter's index holds (emails_count.personal for named people, emails_count.generic for role addresses like info@). Use it to size a batch, not to list contacts.

  • "How many contacts could I reach across these companies?" → call Find-People. To size a specific selection, pass the exact domains of the displayed/selected companies — not the original query, which re-counts every company matching the search and overstates the budget. Present the totals so the user can budget credits before running Domain Search.
  • "Find the CTOs / VPs of Sales / marketing leaders" (actual named people by role) → this is not a Find-People call. Run Find-Companies for the segment, then Domain-Search on each company's domain with the role mapped to server-side filters (seniority: "executive", department: "it", etc. — see the domain-search skill). For the end-to-end version, hand off to the prospecting skill.

Saved Searches

  • Reuse an existing saved search → List-Saved-Searches to show the user's saved searches, Get-Saved-Search to load one's stored filters. Find-Companies/Find-People can't re-apply the stored structured filters verbatim, so the natural-language query you reconstruct is approximate — present it to the user to confirm or refine before re-running Find-Companies, so a complex saved search doesn't return an unexpected scope.
  • Create a saved search → Create-Saved-Search stores a structured filters payload. After a Find-Companies run, pass the meta.filters from that response to Create-Saved-Search to save the current search. (A bare natural-language string with no filters payload can't be saved this way.)
  • Delete a saved search → confirm the name first, then Delete-Saved-Search.

Credit Cost

  • Find-Companies, Find-People (counts), and all saved-search operations — Free (no credits).
  • Pulling the actual contacts (Domain Search) and verifying them consumes credits — confirm before doing it in bulk.

Success Criteria

At least one company returned matching the user's criteria — with people-by-role requests correctly routed to Domain Search / prospecting rather than to Find-People.

Source and attribution

Source:hunter-io/claude-plugininskills/discoverat commit44f0f56

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal