Apollo Like Leads Apify

Use this skill when the user needs B2B lead collection via Apify actor LurATYM4hkEo78GVj (Apollo-like), including filter-based payload building, validated ru...

Security Scan

The skill's code, instructions, and required APIFY_TOKEN are consistent with its stated purpose of running an Apify actor to collect Apollo-like B2B leads.

Purpose & Capability

Name/description (run Apify actor LurATYM4hkEo78GVj for B2B leads) matches what the repository and SKILL.md request: a single APIFY_TOKEN and a Python runner that posts to the Apify API.

Instruction Scope

SKILL.md instructs building payloads, running the included script, and handling JSON/CSV outputs. Instructions and script only reference input JSON/files, the APIFY_TOKEN, and Apify API endpoints — no unrelated file reads or external endpoints.

Install Mechanism

There is no install spec (instruction-only skill). The repo includes a Python script (no external dependencies per requirements.txt) which is normal for this workflow. The script performs only standard HTTP calls to api.apify.com.

Credentials

The skill only requires APIFY_TOKEN, which is appropriate. Minor metadata inconsistency: registry metadata listed no primary credential while SKILL.md marks APIFY_TOKEN as the primary credential; functionally the script uses APIFY_TOKEN correctly.

Persistence & Privilege

The skill does not request always:true or other elevated persistence and does not modify other skills or system-wide settings. It can be invoked autonomously (platform default), which is expected for skills.

Assessment

This skill is coherent: it runs the Apify actor identified in the description and needs only your APIFY_TOKEN. Before installing, verify the actor ID on Apify, use a scoped token (not a broad or long-lived personal credential), and test with small runs (max_results 50–200). Be aware the script will make network calls to api.apify.com (it does not call other endpoints). Also confirm that collecting and using scraped contact data complies with applicable laws and the target services' terms of use. If you don't want autonomous agent invocation, disable model invocation when installing or only grant the skill to trusted agents. Note the repository metadata has a small mismatch about which field is the primary credential — functionally the script uses APIFY_TOKEN as expected.

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