Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against Supabase.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
La commande reste sur une seule ligne. Faites défiler horizontalement pour la vérifier avant de la copier.
Vous préférez une copie locale ? Téléchargez les fichiers actuellement disponibles dans SkillsMP.
Explorateur de fichiers
27 fichiers
Affichage de SKILL.md
SKILL.md
Instructions source · Aperçu en lecture seule
Plus depuis ce dépôt
name
apollo-lead-finder
description
Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against Supabase.
tags
["lead-generation"]
Apollo 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. Deduplicates against Supabase.
Key advantage over CrustData: 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 (One-Time Setup)
1. Apollo API Key
Get your API key from Apollo.io Settings > Integrations > API. Add to .env:
APOLLO_API_KEY=your-api-key-here
2. Supabase Project
Same Supabase project used by crustdata-supabase. The full schema lives in tools/supabase/schema.sql. This skill writes to the people table (dedup by linkedin_url UNIQUE constraint). Run python3 tools/supabase/setup_database.py if setting up fresh.
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:
person_titles — job title keywords (array of strings)
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: Save manifest — Write Apollo person IDs + preview data to a JSON manifest file for the enrich phase.
Step 5: Export preview CSV — Write search results to output/{client-name}-search-{timestamp}.csv (limited data — full data after enrichment).
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 upsert leads to Supabase without explicit user approval.
This skill writes to the people table during the enrich phase. The search phase is free and produces no database writes — but enrichment both costs credits AND writes to the database.
Required flow:
Run --phase search first (free) — review the search results and preview CSV
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 upserting to Supabase
Only upsert after the user confirms the results look good
The agent must NEVER pass --yes on a first run. The --yes flag is only for pre-approved automated runs.
If the user hasn't approved the upsert: Export the CSV and show sample results. Let the user review. Only proceed to upsert after they confirm.
Step 1: Load search manifest — Read the manifest JSON saved by the search phase. Contains Apollo person IDs.
Step 2: Connect to Supabase — Fetch existing LinkedIn URLs for 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 Supabase — Filter out leads whose LinkedIn URLs already exist in Supabase.
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: Upsert to Supabase — Only after user approval. Insert net-new people with source='apollo', enrichment_status='complete'.
Step 8: Export CSV — Write enriched leads to output/{client-name}-enriched-{timestamp}.csv. Update manifest to remove enriched people.
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 Supabase 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
Full search + enrich (only for pre-approved repeat runs):
python3 skills/apollo-lead-finder/scripts/apollo_lead_finder.py \
--config skills/apollo-lead-finder/configs/example.json --phase both
Apollo API Reference
People Search:POST https://api.apollo.io/api/v1/mixed_people/api_search — FREE, returns Apollo IDs + preview data (first name, title, org name, boolean flags). No LinkedIn URLs or emails.
People Match (enrich):POST https://api.apollo.io/api/v1/people/match — 1 credit, reveals email/phone
Bulk People Match:POST https://api.apollo.io/api/v1/people/bulk_match — up to 10 per request, 1 credit each
Create List:POST https://api.apollo.io/api/v1/labels — create a named list
Create Contact:POST https://api.apollo.io/api/v1/contacts — add person to Apollo CRM + optional list
Auth:x-api-key: {APOLLO_API_KEY} header on all requests
Rate limit: Varies by plan. Handle 429 with Retry-After header.
Search Pagination:page param (1-indexed), per_page max 100
