A comprehensive AI-driven B2B prospecting tool for finding and enriching company and contact data using the AgentSource database.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lead-enricher-explorium-agentsource
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install lead-enricher-explorium-agentsource 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 AgentSource Skill?
The AgentSource skill is a powerful extension for the Openclaw Skills ecosystem designed to automate B2B market research and sales prospecting. It provides a direct interface to the Explorium AgentSource API, allowing users to search for both businesses and individual prospects using natural language. The skill handles the complex logic of query parsing, filter optimization, and semantic data matching, ensuring that developers and sales professionals can generate high-quality lead lists without manual data entry.
This skill is particularly valuable for those looking to identify high-intent companies based on specific technographics, firmographics, and real-time signals like funding rounds or hiring trends. By integrating this into your Openclaw Skills workflow, you gain the ability to not only find new leads but also to enrich existing datasets with verified contact information, including emails, phone numbers, and social profiles.
AgentSource Skill Use Cases
- Finding decision-makers and C-suite executives at healthcare or technology companies.
- Identifying businesses that have recently closed a Series A or B funding round.
- Building target lists of companies using specific software stacks like Salesforce or HubSpot.
- Enriching local CSV files with missing contact details and firmographic data.
- Tracking buying intent signals for specific industry topics to prioritize sales outreach.
How AgentSource Skill Works
- The skill analyzes the user's natural language request to determine the entity type (businesses or prospects) and relevant filters.
- It performs semantic autocomplete on fields such as job titles or industry categories to match the AgentSource database taxonomy exactly.
- A market sizing check is executed to provide a free count of total matching results before any credits are spent.
- A small sample of results is fetched and displayed to the user as a preview for validation.
- Once the user confirms, a full fetch is initiated, with the skill automatically handling pagination and data aggregation.
- Optional enrichment layers (like contact info or tech stack) and event data are applied to the fetched records.
- The final processed dataset is exported to a local CSV file for use in CRM or outreach tools.
AgentSource Skill Setup
To use this skill within your Openclaw Skills environment, you must have an Explorium API key.
# 1. Locate or install the CLI tool
# The skill looks for agentsource.py in ~/.agentsource/bin/
# 2. Configure your API key (saves to ~/.agentsource/config.json)
python3 ~/.agentsource/bin/agentsource.py config --api-key YOUR_EXPLORIUM_API_KEY
# 3. Alternatively, set an environment variable
export EXPLORIUM_API_KEY="your-key-here"
AgentSource Skill Data Schema & Taxonomy
The skill organizes data using a structured pipeline of JSON temp files and CSV outputs:
| Data Type | Description | Key Fields |
|---|---|---|
| Business Entity | Corporate firmographics and metadata | business_id, name, domain, tech_stack, industry |
| Prospect Entity | Individual contact and professional data | full_name, job_title, email, linkedin, business_id |
| Event Data | Temporal signals and triggers | event_name, event_time, funding_amount, department |
| Statistics | Market sizing metadata | total_results, filters_applied |
| CSV Export | Final portable dataset | Standardized columns for CRM import |
AgentSource Skill Advanced Features
- Semantic Autocomplete: Uses AI to map vague user terms to precise database categories for higher accuracy.
- Bulk Enrichment: Processes existing local CSV lists to append missing data points like emails and company size.
- Event-Based Triggers: Filters results by recent funding rounds, hiring signals, or changes in leadership.
- Relational Chaining: Allows users to find specific companies first and then automatically pivot to find the decision-makers at those exact firms.
- Buying Intent Integration: Targets businesses showing active interest in specific technological or business topics.
SKILL.md
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