---

name: apollo-like-leads-apify description: Use this skill when the user needs B2B lead collection via Apify actor LurATYM4hkEo78GVj (Apollo-like), including filter-based payload building, validated run execution, and JSON/CSV-ready lead output for outreach workflows. required_env_vars:

• APIFY_TOKEN required-env-vars:
• APIFY_TOKEN primary_credential: APIFY_TOKEN primary-credential: APIFY_TOKEN metadata: short-description: Run Apollo-like B2B leads actor via Apify openclaw: requires: env: - APIFY_TOKEN primaryCredential: APIFY_TOKEN

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Apollo-like B2B Leads (Apify Actor)

Overview

This skill runs the Apify actor LurATYM4hkEo78GVj to collect Apollo-style B2B leads with filters such as job title, seniority, location, employee size, industry, and email quality.

Actor link:

• https://console.apify.com/actors/LurATYM4hkEo78GVj/source

Use this skill when a user asks to:

• collect B2B contacts similar to Apollo workflows
• fetch leads with verified emails and optional phones
• build payloads for founders/execs by geo and industry
• run repeatable lead collection from script/API

Scope

• Build validated actor input payloads.
• Run actor with secure token handling (APIFY_TOKEN env or --apify-token).
• Return normalized summary and raw lead rows.
• Support quick preset runs and custom JSON input.

Step-by-step workflow

1. Confirm target ICP (titles, seniority, location, company size, industries).
2. Build payload with required lead count and enrichment switches.
3. Run actor using scripts/apollo_like_leads_actor.py.
4. Validate lead count and inspect sample rows.
5. Export rows to n8n/Sheets/CSV as needed.

Authentication

Preferred:

export APIFY_TOKEN='apify_api_xxx'

Alternative:

python3 scripts/apollo_like_leads_actor.py run \
  --apify-token 'apify_api_xxx' \
  --input-json '{"max_results":50,"person_location_country":["United States"]}'

Quick start commands

1) Preset: 50 US founders (verified emails)

APIFY_TOKEN='apify_api_xxx' \
python3 scripts/apollo_like_leads_actor.py quick-founders-us-50

2) Custom run from inline JSON

APIFY_TOKEN='apify_api_xxx' \
python3 scripts/apollo_like_leads_actor.py run \
  --input-json '{
    "max_results": 1000,
    "job_titles": ["CEO", "Founder", "Co-Founder"],
    "job_title_seniority": ["owner", "cxo"],
    "person_location_country": ["United States"],
    "employee_size": ["11-50", "51-200", "201-500"],
    "email_status": "verified",
    "include_emails": true,
    "include_phones": false
  }'

3) Custom run from JSON file

APIFY_TOKEN='apify_api_xxx' \
python3 scripts/apollo_like_leads_actor.py run \
  --input-file references/sample_input.json

Output contract

Script returns JSON with:

• ok
• actorId
• leadsCount
• inputUsed
• rows[]

You can pass rows directly to n8n HTTP/Code nodes or map into Google Sheets columns.

Important rules

• Do not hardcode API keys in workflow templates.
• Keep max_results realistic for testing first (e.g., 50-200).
• Use email_status: "verified" for higher outreach quality.
• If the user wants phone-heavy output, set include_phones: true explicitly.
• Seniority values should match actor enum (owner, cxo, vp, director, etc.); this script auto-normalizes common Apollo values like founder -> owner.

References

• references/actor-input-guide.md
• references/troubleshooting.md