bcharleson/clay-gtm-cli/clay-icp-score

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npx vskill@latest install bcharleson/clay-gtm-cli/clay-icp-score

SKILL.md

clay-icp-score — ICP Qualification Scoring

Score a lead or account against your Ideal Customer Profile (ICP). Returns a fit score and signal breakdown so you can prioritize outreach. Combines company size, industry, tech stack, funding, and persona seniority signals.

install

bash
npm install -g clay-gtm-cli
brew install cloudflared
clay tables add \
--name icp-score \
--webhook-url https://app.clay.com/webhook/YOUR_WEBHOOK_ID \
--description "ICP scoring — returns fit score + signal breakdown"
clay listen start

commands

bash
# Score a lead by LinkedIn URL (person + company enriched in Clay)
clay fire icp-score \
--data '{"linkedin_url": "https://linkedin.com/in/jdoe"}' \
--wait
# Score by domain (account-level only)
clay fire icp-score \
--data '{"domain": "acme.com"}' \
--wait
# Score with pre-enriched data (faster, skips re-enrichment)
clay fire icp-score \
--data '{
"first_name": "Jane",
"last_name": "Smith",
"title": "Head of Revenue Operations",
"company": "Acme Corp",
"domain": "acme.com",
"employee_count": 350,
"industry": "SaaS",
"funding_stage": "Series B"
}' \
--wait

output

json
{
"success": true,
"table": "icp-score",
"data": {
"icp_score": 87,
"icp_tier": "A",
"signals": {
"company_size_fit": true,
"industry_fit": true,
"funding_stage_fit": true,
"persona_fit": true,
"tech_stack_fit": false,
"hiring_signal": true
},
"score_breakdown": {
"company_size": 20,
"industry": 20,
"funding_stage": 15,
"persona_seniority": 20,
"tech_stack": 0,
"hiring_signal": 12
},
"recommended_action": "high_priority_outreach",
"notes": "Series B SaaS, RevOps leader, actively hiring SDRs — strong buying signal"
}
}

ICP tiers:

  • A (80-100): Immediate outreach — high-priority
  • B (60-79): Good fit — standard sequence
  • C (40-59): Marginal fit — nurture only
  • D (<40): Poor fit — do not contact

clay table setup

In your Clay table:

  1. Trigger: Webhook
  2. Steps: Person Enrichment, Company Enrichment, AI scoring formula (use Clay's AI column or conditional scoring columns), Tier assignment
  3. Final step: HTTP API → POST to {{_callback_url}} with icp_score, icp_tier, signals, recommended_action

common patterns

bash
# Only return A-tier leads
clay fire icp-score \
--data '{"linkedin_url": "https://linkedin.com/in/jdoe"}' \
--wait | jq 'select(.data.icp_tier == "A")'
# Score and route to correct sequence
RESULT=$(clay fire icp-score \
--data '{"linkedin_url": "https://linkedin.com/in/jdoe"}' --wait)
TIER=$(echo $RESULT | jq -r '.data.icp_tier')
case $TIER in
A) echo "Add to high-touch sequence" ;;
B) echo "Add to automated sequence" ;;
C) echo "Add to nurture" ;;
D) echo "Skip" ;;
esac
# Batch score a list and filter for A+B only
cat prospects.json | jq -c '.[]' | while read lead; do
clay fire icp-score --data "$lead" --wait \
| jq 'select(.data.icp_tier == "A" or .data.icp_tier == "B") | .data'
done
# Get score breakdown to understand why a lead scored low
clay fire icp-score \
--data '{"domain": "somecompany.com", "linkedin_url": "https://linkedin.com/in/janedoe"}' \
--wait --pretty | jq '.data.score_breakdown'

row limit

bash
clay usage show icp-score
clay tables reset icp-score --webhook-url https://app.clay.com/webhook/NEW_ID

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