janskuba/go-to-market-orchestrator/lead-enrichment

Claude Code and agent skill by janskuba/go-to-market-orchestrator

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Enrich a list of companies or contacts with firmographic, technographic, and contact data using available APIs.

Install

npx vskill@latest install janskuba/go-to-market-orchestrator/lead-enrichment

SKILL.md

Lead Enrichment

Task

Take a raw list of companies or contacts and enrich each record with structured data from available APIs and web sources. Output a clean, analysis-ready dataset.

Input Requirements

  • A CSV or JSON file containing at least one of:
  • Company names or domains
  • Contact names + company
  • LinkedIn profile URLs
  • File path: provide the path to the input file
  • Enrichment level: basic (company data only) or full (company + contact + signals)

Instructions

  1. Read the input file and validate the format. Flag any rows missing required fields.
  2. For each company, pull:
  • Employee count, revenue estimate, industry, founding year
  • Headquarters location, other office locations
  • Funding history (total raised, last round, date)
  • Tech stack (from BuiltWith, job postings, or similar)
  • Recent news (funding, hiring, product launches)
  • LinkedIn company page URL
  • For Tier 1 prospects, use Perplexity for deeper research: recent company news, executive interviews, strategic priorities, competitive moves. This context powers stronger personalization.
  1. For each contact (if full enrichment):
  • Verified email address
  • Current title and seniority level
  • LinkedIn profile URL
  • Time in current role
  • Previous companies
  1. Score each record against the ICP definition in your CLAUDE.md:
  • Tier 1 / Tier 2 / Tier 3 based on scoring rubric
  • Flag records that don't meet minimum ICP criteria
  1. Check exclusion rules: remove any records matching competitor domains, existing customers, or DNC lists
  2. Write a personalization note for each Tier 1 and Tier 2 prospect: one sentence referencing their strongest signal

Output Format

CSV file with these columns:

company_name, company_domain, industry, employee_count, revenue_estimate, funding_stage, last_funding_date, tech_stack, hq_location, contact_name, contact_email, contact_title, contact_linkedin, seniority, signal, tier_score, personalization_note, exclude_reason
  • Save to: ./data/enriched/[INPUT_FILENAME]_enriched.csv
  • Log summary: total records processed, records enriched, records excluded, tier distribution

Example Usage

/lead-enrichment
Input: ./data/prospects/saas_companies_march.csv
Enrichment level: full

Output: ./data/enriched/saas_companies_march_enriched.csv with 150 records enriched, 12 excluded (3 competitors, 5 existing customers, 4 below ICP minimum), tier distribution: 34 Tier 1, 67 Tier 2, 37 Tier 3.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

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