Goose-skills apollo-lead-finder
git clone https://github.com/gooseworks-ai/goose-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/gooseworks-ai/goose-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/capabilities/apollo-lead-finder" ~/.claude/skills/gooseworks-ai-goose-skills-apollo-lead-finder && rm -rf "$T"
skills/capabilities/apollo-lead-finder/SKILL.mdApollo Lead Finder
Two-phase Apollo.io prospecting: free People Search for lead discovery, then selective paid enrichment to reveal emails and phone numbers. Creates Apollo lists and contacts.
Key advantage: Apollo People Search is free (no credits consumed). Credits are only spent when enriching contacts to reveal email/phone. This lets you search tens of thousands of leads at zero cost, review results, then selectively enrich only the best matches.
Prerequisites
Apollo API Key
Get your API key from Apollo.io Settings > Integrations > API. Add to
.env:
APOLLO_API_KEY=your-api-key-here
That's it — one env var.
Phase 0: Intake
Ask the user these questions to build the Apollo filter config:
ICP Criteria
- What job titles are you targeting? (e.g., "VP of Sales", "Head of Growth")
- What seniority levels? Options: owner, founder, c_suite, partner, vp, director, manager, senior, entry
- Company size (employee range)? Format: "51,200" "201,500" "501,1000" "1001,5000"
- Geographic regions? (e.g., "United States", "San Francisco, California")
- Industry/keyword tags? (e.g., "SaaS", "Software", "FinTech")
- Any titles to exclude? (e.g., "intern", "assistant")
- Should we create an Apollo list with these contacts? (default: yes)
- How many results do you want? (test: 100, standard: 5,000, full: 50,000)
Map Answers to Config
Build the config JSON with Apollo's filter format:
{ "client_name": "example-client", "search_config_name": "vp-sales-us-midmarket", "icp_segment": "sales-leaders", "apollo_filters": { "person_titles": ["VP of Sales", "Head of Sales", "Director of Sales"], "person_seniority": ["vp", "director"], "person_locations": ["United States"], "organization_num_employees_ranges": ["51,200", "201,500", "501,1000"], "q_organization_keyword_tags": ["SaaS", "Software"] }, "enrichment_filters": { "exclude_titles_containing": ["intern", "assistant"] }, "apollo_list_name_prefix": "example-sales-leaders", "create_apollo_list": true, "mode": "standard", "max_pages": 50 }
Available Apollo search filters:
— job title keywords (array of strings)person_titles
— seniority levels: owner, founder, c_suite, partner, vp, director, manager, senior, entryperson_seniority
— geographic locations (array of strings)person_locations
— employee count ranges, format "min,max" (e.g., "51,200")organization_num_employees_ranges
— company keyword tags (e.g., "SaaS", "Software")q_organization_keyword_tags
— titles to exclude (array of strings)person_not_titles
— organization name searchq_organization_name
— company HQ locationsorganization_locations
Phase 1: Search (FREE)
What the free search returns
Apollo's
api_search endpoint returns limited preview data: Apollo person ID, first name, obfuscated last name, title, company name, and boolean flags (has_email, has_phone). No LinkedIn URLs, emails, or full names — those require enrichment.
Pipeline Steps
Step 1: Build Apollo search payload — Map config filters to Apollo People Search format.
Step 2: Search page 1 — Get first 100 results +
total_entries for total count.
Step 3: Paginate — Fetch remaining pages (100 per page, up to mode cap). Apply title filters.
Step 4: Collect Apollo person IDs — Store the Apollo person IDs from search results for the enrich phase.
Step 5: Present preview — Show the user a sample of search results (first name, title, company) and total count. Ask for approval before enriching.
Mode Caps
| Parameter | Test | Standard | Full |
|---|---|---|---|
| Max pages | 1 | 50 | 500 |
| Max results | 100 | 5,000 | 50,000 |
| Search credits | 0 | 0 | 0 |
Cost: FREE. People Search does not consume Apollo credits.
Database Write Policy
CRITICAL: Never export leads without explicit user approval.
The search phase is free. The enrich phase costs credits.
Required flow:
- Run search first (free) — review the results
- Present search results to the user: total matches, sample leads, title distribution
- Get explicit user approval before running enrich phase
- After enrichment, present the enriched results to the user before exporting
- Only export after the user confirms the results look good
Phase 2: Enrich (COSTS CREDITS)
Use the Apollo Bulk People Match API to enrich selected leads from Phase 1.
Pipeline Steps
Step 1: Load search manifest — Read the manifest JSON saved by the search phase. Contains Apollo person IDs.
Step 2: Load existing contacts for dedup — If the user has a CSV of existing contacts or a previous export, load LinkedIn URLs for dedup. If no existing data, skip dedup.
Step 3: Confirm credits — Display lead count and credit cost estimate. Wait for confirmation.
Step 4: Bulk enrich — Call
/people/bulk_match with Apollo person IDs in batches of 10. Each match costs 1 credit. Returns full data: email, phone, LinkedIn URL, full name, location, company details.
Step 5: Dedup against existing contacts — Filter out leads whose LinkedIn URLs already exist in the user's contact list.
Step 6: Present results to user — Show enriched sample leads (names, titles, companies, email coverage) and ask for explicit approval before writing to the database.
Step 7: Export results — Only after user approval. Save enriched leads as CSV to the current working directory, or wherever the user prefers.
Mode Caps
| Parameter | Test | Standard | Full |
|---|---|---|---|
| Max enrichments | 10 | 500 | 2,500 |
| Credits used | 10 | 500 | 2,500 |
Cost: 1 credit per contact enriched. Always run search first, review results, then selectively enrich.
Phase 3: Review & Refine
Present results:
- Total matching — how many profiles match the filters in Apollo
- New leads found — net-new profiles (after dedup)
- Apollo list — name and link to the list in Apollo
- Enriched — how many have emails revealed
- Email coverage — percentage of enriched leads with valid emails
- Top 10 leads — name, title, company preview
Common adjustments:
- Too broad — add more filters (seniority, employee range, keyword tags)
- Too narrow — broaden title list, remove location filters
- Low email coverage — some contacts genuinely have no known email; try enriching more leads
- Wrong ICP — adjust title include/exclude lists
Example Usage
Trigger phrases:
- "Search Apollo for [titles] at [industries]"
- "Find leads in Apollo matching my ICP"
- "Find VP of Sales at SaaS companies in the US"
- "Enrich the Apollo leads from last search"
Apollo API Reference
- People Search:
— FREE, returns Apollo IDs + preview data (first name, title, org name, boolean flags). No LinkedIn URLs or emails.POST https://api.apollo.io/api/v1/mixed_people/api_search - People Match (enrich):
— 1 credit, reveals email/phonePOST https://api.apollo.io/api/v1/people/match - Bulk People Match:
— up to 10 per request, 1 credit eachPOST https://api.apollo.io/api/v1/people/bulk_match - Create List:
— create a named listPOST https://api.apollo.io/api/v1/labels - Create Contact:
— add person to Apollo CRM + optional listPOST https://api.apollo.io/api/v1/contacts - Auth:
header on all requestsx-api-key: {APOLLO_API_KEY} - Rate limit: Varies by plan. Handle 429 with Retry-After header.
- Search Pagination:
param (1-indexed),page
max 100per_page