data-enrichment-strategy SKILL.md skillA
data-enrichment-strategy from leadmagic/gtm-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add leadmagic/gtm-skills/data-enrichment-strategy@v1.0.1Pins v1.0.1 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- leadmagic/gtm-skills
- Path
skills/prospecting/data-enrichment-strategy/SKILL.md- Versions recorded
- 6
- Latest version
- v1.0.1, committed Oct 1, 2026
- First version recorded
- Jun 8, 2026
- Size
- 8,358 bytes
- Repository stars
- 76
- License
- MIT
Design an end-to-end B2B data enrichment architecture — provider selection, waterfall design, cost modeling, and CRM hygiene. Use when the user wants to evaluate enrichment providers, build an enrichment stack, compare data vendors, or design their data architecture. Triggers on: "enrichment strategy", "which data provider", "compare Apollo vs ZoomInfo", "build enrichment architecture", "data stack", "enrichment vendors", or any request about choosing or combining B2B data sources.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Data Enrichment Strategy ## Overview Every B2B go-to-market team needs enrichment. No single provider covers everything, and the stack you choose determines your data quality, cost structure, and operational complexity for years. This skill walks through provider selection, waterfall architecture design, build-vs-buy decisions, and ongoing data hygiene. The output is a complete enrichment architecture tailored to the user's ICP, budget, and volume. ## When to Use - "What enrichment providers should we use?" - "Apollo vs ZoomInfo vs Clay — which is right for us?" - "Design our data enrichment architecture" - "How do we get 90%+ email coverage?" - "Should we build or buy our enrichment pipeline?" ## Authoritative Foundations The enrichment provider landscape is well-documented by DAMA-DMBOK, Open Data Institute, Ziellab, and the GTM engineering community. The core design principle: no single provider covers more than 60-75% of B2B contacts. Waterfall enrichment — chaining multiple providers in sequence — is the standard pattern for hitting 85-92% coverage. Three separate waterfalls (company, email, phone) is the Ziellab architecture: …
Read the whole file at its exact version.
How to install
mdr add leadmagic/gtm-skills/data-enrichment-strategy@sha256:332cd77593db3d59The line at the top of this page pins the label v1.0.1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_zutuvdrtm4a4oeha)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 6 versions of this file, between Jun 8, 2026 and Oct 1, 2026, about one every 23 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.1 latest | 2026-10-01 | ca0d2ec | 8,358 B | A | view · diff |
| v1.0.1 | 2026-09-07 | 92666c2 | 8,365 B | A | view · diff |
| v1.0.0 | 2026-09-02 | a19750a | 8,024 B | A | view · diff |
| v1.0.0 | 2026-06-10 | 17b6e1f | 8,018 B | A | view · diff |
| v1.0.0 | 2026-06-10 | 9f00d65 | 8,019 B | A | view · diff |
| v1.0.0 | 2026-06-08 | 07ce0cd | 7,780 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (8358 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
leadmagic/gtm-skills · 76 stars · license MIT · pushed 2026-10-14 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_zutuvdrtm4a4oeha GET https://markdownregistry.com/api/v1/resolve?ref=leadmagic/gtm-skills/data-enrichment-strategy GET https://markdownregistry.com/api/v1/blob/332cd77593db3d598cbe4eb796984acaac1546c12570127caa35071f1234c707
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.