Lead Scraper for Openclaw

An intelligent automated tool for collecting, cleaning, and classifying potential customer leads from multiple business and social platforms.

wensen2024
v1.0.2
Apr 3, 2026
0
1.9k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install lead-scraper

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install lead-scraper using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Lead Scraper?

Lead Scraper is a robust automation tool built for the Openclaw Skills ecosystem, designed to help businesses rapidly build high-quality sales pipelines. It automates the extraction of publicly available information from major corporate databases, B2B marketplaces, and professional social networks. Beyond simple extraction, the tool focuses on data integrity by providing automated cleaning, de-duplication, and intelligent classification to ensure sales teams work only with the most relevant and accurate data.

Lead Scraper Use Cases

  • Targeted industry searches to find company contact information in specific geographical regions.
  • Keyword-based lead extraction for niche markets like intelligent manufacturing or green energy.
  • Automated harvesting of exhibitor and participant data from major trade shows and industry conferences.
  • Batch processing of existing contact lists to remove duplicates and append missing information.
  • High-intent prospect identification through automated lead quality scoring and prioritization.

How Lead Scraper Works

  1. The user initiates a request via natural language or CLI specifying the target industry, location, or platform source.
  2. The skill queries configured public platforms such as Qichacha, LinkedIn, or 1688 while adhering to robots.txt protocols.
  3. Collected raw data is processed through a cleaning engine that standardizes formats and filters out invalid or redundant entries.
  4. An AI-driven scoring system evaluates each lead based on company scale, industry relevance, and inferred intent.
  5. The final refined dataset is organized and exported into the user's preferred format, such as Excel, CSV, or direct CRM integration.

Lead Scraper Setup

Lead Scraper is ready for use within Openclaw Skills with no mandatory hardware configuration. You can customize the behavior by editing your configuration file:

# Example: Scraping e-commerce leads in Hangzhou via the CLI
scrape "Hangzhou region e-commerce industry contact info"

Optional configuration for power users:

{
  "skills": {
    "entries": {
      "lead-scraper": {
        "config": {
          "platforms": ["qichacha", "tianyancha"],
          "rate_limit": 100,
          "output_format": "xlsx"
        }
      }
    }
  }
}

Lead Scraper Data Schema & Taxonomy

The skill generates structured reports and datasets with the following metadata taxonomy:

Attribute Description
Company Name The official registered name of the business entity.
Contact Info Publicly available phone numbers, emails, and addresses.
Industry/Scale Categorization by business sector and company size.
Lead Score A 1-10 quality rating based on industry fit and intention.
Source Platform The origin of the data (e.g., LinkedIn, B2B site).
Follow-up Sug. AI-generated recommendations for outreach timing and scripts.

Lead Scraper Advanced Features

  • Multi-platform aggregation combining corporate records with social media profiles.
  • Intelligent lead scoring to identify high-priority prospects automatically.
  • Comprehensive data hygiene tools for cleaning and enriching external CSV/Excel files.
  • Direct CRM mapping for seamless transition from lead extraction to sales follow-up.
  • Compliance-first architecture that strictly processes only publicly accessible data.

SKILL.md


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