Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swan-gtm/gtm-skills --skill clay-enrichment-9stepgit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/clay-enrichment-9step)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/clay-enrichment-9step"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/clay-enrichment-9step/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/clay-enrichment-9step"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/clay-enrichment-9step.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.00611 |
| Opus 5 | $0.00026 | $0.00305 |
| Sonnet 5 | $0.00010 | $0.00122 |
| Haiku 4.5 | $0.00005 | $0.00061 |
Grade A, and why
clay-enrichment-9step scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- clay-enrichment-9step — 92% identical, 4 lines differ
What it actually says
Clay 9-Step Enrichment Workflow (90%+ Coverage)
For detailed templates, see references/templates.md.
Quick Reference
| Step | Action | Tools |
|---|---|---|
| 1 | Upload & Clean | CSV import |
| 2 | Company Enrichment | Apollo, Ocean.io, LinkedIn |
| 3 | People Enrichment | Sales Navigator, Apollo |
| 4 | Email Waterfall | Apollo, Prospeo, LeadMagic, Findymail |
| 5 | Email Verification | MillionVerifier |
| 6 | Phone Numbers | LeadMagic, BetterContact |
| 7 | Custom Data | Claygent |
| 8 | Scoring | Lead scoring (100 pts) |
| 9 | Export | Instantly, LemList, CRM |
Step 4: Email Waterfall (The Money Step)
Single finder = 40% coverage Waterfall = 85%+ coverage
Sequence: Apollo → Prospeo → LeadMagic → Findymail → Clay patterns
Step 8: Scoring & Segmentation
Lead Score (100 points):
- Company size match: 25 pts
- Recent signals: 25 pts
- Email deliverability: 25 pts
- ICP fit: 25 pts
Tiers:
- Tier 1 (80-100): Immediate outreach
- Tier 2 (60-79): Nurture sequence
- Tier 3 (<60): Long-term nurture
Pro Tips
- Run in batches of 250 (optimizes Clay credits)
- Test with 50 records first before full run
- Timeline: 1,000 prospects = 2-3 hours vs 40+ hours manual
Combines with
| Skill | Why |
|---|---|
clay-buying-signals-5 |
Add signal detection to workflow |
lead-sources-guide |
Know where to source initial data |
ai-personalization-prompts |
Use Claygent for AI personalization |
buying-signals-6 |
Understand which signals to track |
Example prompts
Set up a Clay workflow for job change signals with email waterfall.
How do I configure Step 4 (Email Waterfall) to maximize coverage?
Create a scoring model for SaaS companies targeting enterprise accounts.
Part of Frontal — free, open GTM skills for your AI agent. Browse the library →
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 81 lines · 51 tokens per session scan A ae042ec333b9
clay-enrichment-9step is a skill published in the GitHub repository swan-gtm/gtm-skills (150 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 611 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
afrexai-lead-hunter
Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.
first-customer-finder
Find and qualify evidence-backed potential first customers, early adopters, design partners, or beta users for a startup using recent public pain and buying signals. Use when Codex needs to analyze a product URL or idea, define an ideal customer profile, research public discussions and business pages, identify…
reddit-leads
Discover B2B leads from Reddit using AI-powered lead scoring via reddapi.dev Leads API. Finds high-intent signals, scores them 0-100, and classifies by lead type (painpoint, solutionrequest, complaint, featurerequest, comparison). Perfect for competitor poaching, pain point discovery, and sales prospecting.
lead-gen
Use when building and qualifying a prospect list before anyone reaches out — a falsifiable ICP, named accounts/contacts from Apollo/ZoomInfo/Clay, deduped against the CRM, tiered by fit+intent+engagement. NOT writing or sending the outreach (that is cold-outreach), NOT tracking the deal after first contact (that is…
Lead Research Assistant
Research company and contact information for sales outreach.
first-customer-finder
Find and qualify evidence-backed potential first customers, early adopters, design partners, or beta users for a startup from recent public signals. Trigger on "find my first customers", "who would buy this", "find early adopters", "find design partners", "find beta users", "find leads for my startup", or when given a…