waterfall-enrichment

waterfall-enrichment is a skill for Claude Code from LeadMagic/gtm-skills. It costs 46 tokens per session (1,189 once invoked), scanned A, original, MIT.

A method for combining several business-data providers in a fallback sequence, called a waterfall, to find company, email, and phone information.

In plain words
What is it for?
Use it to design separate enrichment workflows for company, email, and phone data, choose provider order, and add verification.
Why use it?
A single provider may have incomplete records, so trying additional providers can improve coverage while controlling lookup costs and checking the results.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code; mentions Codex; mentions Gemini CLI.

Part of the gtm-skills plugin — 196 skills shipped together

Good fit Use it to design separate enrichment workflows for company, email, and phone data, choose provider order, and add verification.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/leadmagic/gtm-skills/waterfall-enrichment
Install

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.

Any agent
npx skills add LeadMagic/gtm-skills --skill waterfall-enrichment
Clone the repo
git clone --depth 1 https://github.com/LeadMagic/gtm-skills

Made for: Claude Code.

Or install gtm-skills, the plugin that ships this one along with the rest of its 196 skills.

Wrote 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.

agentmods badge for waterfall-enrichment

README.md
[![agentmods](https://agentmods.dev/badge/skills/leadmagic/gtm-skills/waterfall-enrichment/github.svg)](https://agentmods.dev/skills/leadmagic/gtm-skills/waterfall-enrichment)
Your own site
<a href="https://agentmods.dev/skills/leadmagic/gtm-skills/waterfall-enrichment"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/waterfall-enrichment/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.

agentmods 80×15 button for waterfall-enrichment

Your own site · 80×15
<a href="https://agentmods.dev/skills/leadmagic/gtm-skills/waterfall-enrichment"><img src="https://agentmods.dev/badge/skills/leadmagic/gtm-skills/waterfall-enrichment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,189 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.01189
Opus 5 $0.00023 $0.00594
Sonnet 5 $0.00009 $0.00238
Haiku 4.5 $0.00005 $0.00119

Measured 8d ago against content hash 4bf7c96f65f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

waterfall-enrichment 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 8d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check-output.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/automation/waterfall-enrichment/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Waterfall Enrichment

Overview

No single B2B data provider covers more than 60-75% of contacts. A multi-provider waterfall chains providers in sequence, each firing only when the previous returns empty. The result: 85-92% coverage at optimized cost.

This skill covers complete waterfall architecture: 3 separate waterfalls for company data, email, and phone — each with independently optimized provider ordering and verification integration.

Authoritative Foundations

  • DAMA-DMBOK Data Quality Dimensions — Shapes deliverables for this skill — No single B2B data provider covers more than 60-75% of contacts.
  • Ziellab 3-Waterfall Architecture — Shapes deliverables for this skill — No single B2B data provider covers more than 60-75% of contacts.
  • HubSpot Academy — CRM Automation — Lifecycle stages, object model, and workflow enrollment patterns.

When to Use

  • "Build an enrichment waterfall"
  • "Improve our data coverage"
  • "Chain multiple enrichment providers"
  • "Design a cost-optimized enrichment pipeline"
  • "Set up waterfall enrichment in Clay"

Step-by-Step Process

Phase 1: Three Separate Waterfalls

Build independent waterfalls for different data types:

Company Waterfall:

  1. Clay native / Clearbit (cheap, broad)
  2. Apollo Company (mid-cost, good SMB coverage)
  3. ZoomInfo (expensive, enterprise depth)
  4. Claygent AI research (unstructured, last resort)

Email Waterfall:

  1. LeadMagic Email Finder (verified results, pay-per-result)
  2. Apollo (270M+ contacts, subscription)
  3. Hunter.io (domain-pattern matching)
  4. People Data Labs (alternative sourcing)
  5. Claygent (AI web research)

Phone Waterfall:

  1. Apollo (mobile, included in subscription)
  2. Cognism (strong EU mobile coverage)
  3. ContactOut (alternative sourcing)
  4. People Data Labs (broad but thinner)

Phase 2: Provider Ordering

Sort by cost-per-hit, not cost-per-attempt. A cheap provider with 20% hit rate costs more per successful lookup than a moderate provider with 70% hit rate.

Read the full file on GitHub · 138 lines

Files

What ships with it

3 files 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.

Changes

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.

  1. 8d ago Changed 4bf7c96f65f9
  2. 12d ago First seen · 138 lines · 46 tokens per session scan A 0bc7de7b7a98

Subscribe to this mod's changes

waterfall-enrichment is a skill published in the GitHub repository LeadMagic/gtm-skills (50 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 1,189 once invoked, about $0.0002 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.

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