enrichment

Enrich prospects with multi-source company data and generate scored outreach briefs.

Updated Feb 19, 2026
One-click install
npx skills add https://github.com/Salahsr01/Cleanbot --skill enrichment
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: enrichment
Source: https://github.com/Salahsr01/Cleanbot/tree/main/workspace/skills/enrichment
Command: npx skills add https://github.com/Salahsr01/Cleanbot --skill enrichment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires trafilatura, lxml, and includes scripts (resource) components.

What problem does it solve?

Centralizes and automates prospect enrichment so teams stop manually resolving company identity, hunting contacts, scraping web content, and crafting outreach; it produces a scored, sendable brief for sales outreach.

Core Features & Use Cases

  • Multi-source identity resolution (Annuaire-Entreprises, Pappers) and domain-to-company matching to avoid false positives.
  • Website scraping with Jina/Trafilatura fallbacks, contact extraction, news aggregation, Hunter.io email discovery, LLM analysis, email generation, rule-based + LLM scoring, and Airtable persistence.
  • Use case: bulk-enrich inbound leads or a single Airtable record to get a prioritized, email-ready outreach sequence with a quality score and suggested CTA.

Quick Start

Run the enrichment pipeline by instructing the assistant to execute: exec pipeline enrich --id recXXXXX

Frequently Asked Questions about enrichment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate prospect enrichment and scoring for French SMEs in Airtable?

You automate prospect enrichment by executing the pipeline with an Airtable record ID, triggering multi-source identity resolution, website scraping, contact extraction, LLM analysis, and scoring to generate a sendable outreach brief.

How does LLM-driven email generation work for B2B outreach briefs?

LLM-driven email generation works by analyzing scraped website content, recent company news, and extracted contacts to produce personalized outreach emails with a quality score and suggested call-to-action for sales teams.

Can I use Trafalatura for website scraping with fallbacks during contact extraction?

Trafalatura is used for deterministic website scraping with Jina fallbacks to ensure content extraction succeeds, enabling subsequent contact extraction and Hunter.io email discovery for comprehensive prospect data.

Does this prospecting pipeline integrate with Hunter.io for email discovery?

The prospecting pipeline integrates with Hunter.io for email discovery, combining scraped website contacts with Hunter.io results to resolve identities and generate personalized outreach emails for French SMEs.

What is the best way to resolve French company identity and avoid false positives in prospecting?

The best way to resolve French company identity and avoid false positives is multi-source matching using Annuaire-Entreprises and Pappers legal data alongside domain-to-company matching before scraping and scoring.

Do I need to use the pipeline executor to run the enrichment process?

You need to invoke the enrichment process via the pipeline executor using the command 'exec pipeline enrich --id recXXXXX' to process a specific Airtable record and generate a scored outreach brief.