From GTM Skills
Builds Clay enrichment workflows: table architecture, waterfall configuration, Claygent AI research, Sculptor table building, CRM push, and credit optimization. Use for building Clay tables, configuring waterfalls, or automating GTM workflows.
How this skill is triggered — by the user, by Claude, or both
Slash command
/gtm-skills:clay-automationThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Clay is the orchestration layer where enrichment, scoring, and routing converge.
Clay is the orchestration layer where enrichment, scoring, and routing converge. Used correctly, it's a GTM multiplier. Used incorrectly, it's a credit-burning machine producing data nobody trusts.
This skill covers when and how to roll out Clay automation — data quality, table separation, rollout phases, and n8n handoff.
Playbook index: references/automation-playbook-index.md — all 38 automation + tool + gtm-ops playbooks.
Automation strategy (before tool config): Jen Igartua (Go Nimbly) — data before AI,
maturity levels 0–4, human+machine division. Canonical → references/gtm-automation-expert-playbook.md
(Pattern 30). Outbound copy/infra → Eric Nowoslawski / Pat Spielmann / Justin Michael — not this skill.
Tool implementation
(table columns, LeadMagic waterfalls, loops) lives in tools/:
clay-toolkit (tools/clay-toolkit) — tables and waterfallsclay-loops-toolkit (tools/clay-loops-toolkit) — signal loopsClay workflow design follows patterns from DAMA-DMBOK data-quality dimensions, Ziellab (3 separate waterfalls: company, email, phone), and GTME Pulse (10 production templates tested at $5M-$100M ARR companies).
The core principle: Clay is a routing engine, not a CRM. Enriched data lives in your CRM; Clay processes it en route.
../../outbound/cold-email-strategy/references/eric-nowoslawski-outbound.md.Rule: separate company and person tables.
Company table: one row per domain. Enriches firmographics, tech stack, company-level qualification once.
Person table: one row per contact. References company data via domain lookup. Enriches email, phone, LinkedIn, role-level qualification.
This separation prevents credit waste from re-enriching the same company data across every contact row.
For each data field, configure a conditional waterfall:
| Field | Primary | Fallback 1 | Fallback 2 |
|---|---|---|---|
| LeadMagic Email Finder | Apollo | Hunter | |
| Phone | Apollo | Cognism | ContactOut |
| Company data | Clay native | Apollo Company | Clearbit |
Set conditions: each fallback only fires when the previous step returns empty or error. Use Clay's conditional logic: "Only run if [previous column] is blank."
Claygent is AI-powered web research. Configure prompts explicitly:
Good prompt: "Find the work email for [name] at [company]. Search the company's team page, LinkedIn profile, and press releases. Return the email AND the source URL. Do NOT guess or construct emails from patterns. If no verified source, return empty."
Bad prompt (don't use): "Find me their email."
Critical rules:
Push enriched data to CRM with a clay_status property:
| clay_status | Meaning | Action |
|---|---|---|
| pending | In enrichment | Hold — not ready |
| enriched | Enrichment complete | Ready for verification |
| verified | Verified and safe | Can enter sequences |
| exported | Pushed to CRM | Done, archive in Clay |
Only contacts with clay_status = verified enter sequences.
Qualify first, enrich deep later. Run ICP filters before expensive contact enrichment. Cuts costs 30-40%.
Credit caps per row. Set max 5-6 credits per row. If a contact is that hard to find, they're probably not a good fit.
Native integrations over HTTP API. Clay's native provider integrations are rate-limited and credit-billed correctly. HTTP API calls bypass Clay's cache and often double-charge.
Batch overnight. Claygent is 15-40s per row. Run large Claygent batches during off-hours.
Clay workflow document with table architecture diagram, provider waterfall configuration, Claygent prompt templates, CRM push rules, credit budget, and maintenance schedule.
One giant table. Combining company and person data wastes credits and makes re-enrichment impossible. Separate always.
Enriching before filtering. Running $0.15-0.40/contact enrichment on non-ICP records wastes budget. Filter on cheap data first.
Claygent guessing emails. Without explicit "do not guess" instructions, Claygent constructs pattern-based emails that bounce at 40-60% rates.
Two-way CRM sync. Clay-to-CRM should be one direction. CRM-to-Clay sync creates data conflicts. Push only.
Clay as permanent storage. Clay is a workspace. Push to CRM, archive or delete rows in Clay. Old rows decay just like anywhere else.
No credit caps. Without caps, a single row can chew through 15+ credits. Cap at 5-6 per row.
references/framework-notes.md — named frameworks, citation anchors, and operating assumptionstemplates/output-template.md — copy-paste deliverable structure for the userscripts/check-output.py — local checklist validator for required sections
This skill includes lightweight artifacts the agent can load on demand:references/gtm-automation-expert-playbook.md — Jen Igartua RevOps automation strategy (repo root; Pattern 30)../../outbound/cold-email-strategy/references/eric-nowoslawski-outbound.md — Crawl Walk Run, Creative Ideas, GEX stack (Eric Nowoslawski)
Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.tools/clay-toolkit — table blueprints, LeadMagic waterfallstools/clay-loops-toolkit — signal loops and routingnpx claudepluginhub leadmagic/gtm-skills --plugin gtm-skillsBuilds Clay tables and enrichment chains using LeadMagic-first waterfalls, Claygent, credit optimization, and CRM push. Use when designing one-time enrichment tables.
Designs production Clay enrichment pipelines using table schemas, waterfall patterns, and CRM sync flows. Useful for new integrations, data flow reviews, or pipeline standards.
Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.