Overview
- Skill Key
- hundevmode/apollo-like-leads-apify
- Author
- hundevmode
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/hundevmode/apollo-like-leads-apify
- Latest Commit SHA
- 42553d394b9afdf19b5845e4cca5a4d6b273998a
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.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 apollo-like-leads-apify 技能。 若已安装,则直接安装 apollo-like-leads-apify 技能。
# 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:
```bash
export APIFY_TOKEN='apify_api_xxx'
```
Alternative:
```bash
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)
```bash
APIFY_TOKEN='apify_api_xxx' \
python3 scripts/apollo_like_leads_actor.py quick-founders-us-50
```
### 2) Custom run from inline JSON
```bash
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_ph...
# Apollo-like B2B Leads Scraper Skill for OpenClaw (Apify Actor) [](./LICENSE) [](https://console.apify.com/actors/LurATYM4hkEo78GVj/source) [](./SKILL.md) This repository provides a production-ready **OpenClaw skill** for running an **Apollo-like B2B leads scraper** through Apify actor [`LurATYM4hkEo78GVj`](https://console.apify.com/actors/LurATYM4hkEo78GVj/source). If you are looking for an **Apollo alternative**, **B2B contact scraper**, **lead generation automation**, or **Apify sales prospecting workflow**, this skill is built for that use case. ## Why this skill Most teams lose time on the same problems: - manually crafting payloads for each target ICP - inconsistent filtering for titles, seniority, geo, and company size - weak credential handling inside scripts and workflows - non-standard outputs that are hard to move into n8n or Google Sheets This skill solves that with: - validated payload execution against a real Apify actor - secure auth using `APIFY_TOKEN` (env var or CLI) - reusable presets (including **50 US founders**) - JSON output ready for n8n, Sheets, and CRM pipelines ## Actor and stack - Apify actor: [`LurATYM4hkEo78GVj`](https://console.apify.com/actors/LurATYM4hkEo78GVj/source) - Runtime: Python 3.10+ - Auth: `APIFY_TOKEN` - Use case: B2B lead scraping, outbound list building, Apollo-style prospecting ## Quick start ### 1) Set token ```bash export APIFY_TOKEN='apify_api_xxx' ``` ### 2) Run preset: 50 US founders ```bash python3 scripts/apollo_like_leads_actor.py quick-founders-us-50 ``` ### 3) Run custom payload from file ```bash python3 scripts/apollo_like_leads_actor.py run --input-file references/sample_input.json ``` ### 4) Run custom payload inline ```bash python3 scripts/apollo_like_leads_actor.py run --input-json '...
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