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lead-enrichment

When the user wants to build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality. Also use when the user mentions 'enrichment,' 'data enrichment,' 'Clay,' 'waterfall enrichment,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'contact verification,' 'Apollo,' 'ZoomInfo,' or 'data quality.' This skill covers lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems. Do NOT use for technical implementation, code review, or software architecture.

Quality

89%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Highly actionable, workflow-oriented content with explicit validation and feedback loops for a batch operation, held back by token bloat. Pricing tables, provider matrices, and benchmarks belong in the existing reference file, and the body's checklists duplicate that file's content.

Suggestions

Move the 'Clay Pricing (2026)' table, Provider Comparison Matrix, Verification Tool Comparison, and Performance Benchmarks sections into references/ (e.g., references/provider-matrix.md), keeping only a decision-rule summary in the body — this also removes the stale-prone dated pricing from the always-loaded context.

De-duplicate the body against references/quick-reference.md: the Deliverability Protection Checklist and credit governance rules overlap the reference file's Enrichment Checklist and Key Metrics tables; keep one canonical location and cross-link.

Promote the pointer to references/quick-reference.md from a single trailing sentence into a clearly signaled 'References' section, and reference it from the sections (Benchmarks, provider selection) whose detail moves out of the body.

DimensionReasoningScore

Conciseness

The body is mostly high-value domain knowledge (scoring weights, provider sequencing, thresholds) with little generic filler, but at ~450 lines it carries stale-prone detail ('Clay Pricing (2026)' price tables), sample ROI arithmetic, and checklists/metrics that duplicate references/quick-reference.md. Not a 4 because the trimming needed — pricing tables, benchmarks, and duplicated checklists — goes beyond minor over-explanation.

3 / 5

Actionability

Fully concrete guidance throughout: exact formulas ('ICP Score = (Firmographic Fit x 0.30) + (Technographic Fit x 0.30) + (Intent Score x 0.40)'), explicit thresholds ('>85% confidence = deliverable', 'Contact within 4 hours'), a column-by-column Clay table spec, worked Examples, and Troubleshooting entries with specific numeric fixes. For an instruction-only skill this is copy-paste-ready and covers the common cases.

5 / 5

Workflow Clarity

The waterfall flow is sequenced explicitly (Pre-qualification → Primary → Secondary → Tertiary → LinkedIn → Verification → Score + Route), and this batch operation has real validation: a 6-step verification pipeline, confidence-score thresholds, a pre-send deliverability checklist, and feedback loops via the Troubleshooting section and per-batch metric tracking with governance alerts. Not a 4 because validation checkpoints and error-recovery loops are explicit, not implicit.

5 / 5

Progressive Disclosure

Sections are well organized and the single reference (references/quick-reference.md) exists and is one level deep, but reference-grade content — the Clay pricing table, provider comparison matrix, and performance benchmarks — is inlined in the body, and the pointer to the reference file is a single mention buried at the very end. Not a 4 because a substantial amount of content that belongs in a separate file is inline and the reference signal is weak.

3 / 5

Total

16

/

20

Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: explicit what-and-when structure, comprehensive natural trigger terms including tool names, and a clear negative boundary. The only weakness is the generic 'data quality' trigger term, which introduces minor conflict risk with non-GTM data-quality requests.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality' — and summarizes coverage as 'lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems', matching the comprehensive multi-action anchor. It is not a 4 because coverage of the skill's capabilities is complete rather than having minor gaps.

5 / 5

Completeness

Both questions are answered explicitly: what ('This skill covers lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems') and when ('When the user wants to build data enrichment workflows... Also use when the user mentions...'), with concrete trigger phrases and an explicit negative boundary ('Do NOT use for technical implementation, code review, or software architecture'). Not a 4 because the 'when' is fully explicit rather than improvable.

5 / 5

Trigger Term Quality

Natural trigger terms include 'enrichment,' 'data enrichment,' 'Clay,' 'waterfall enrichment,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'contact verification,' 'Apollo,' 'ZoomInfo,' and 'data quality' — synonyms plus concrete tool names a user would actually say. It is not a 4 because both common variations and product-specific keywords are present.

5 / 5

Distinctiveness Conflict Risk

The description carves out a clear GTM/lead-enrichment niche with distinct triggers (Clay, Apollo, ZoomInfo, ICP scoring) and an explicit exclusion clause, but the bare trigger 'data quality' is generic and could fire on unrelated data-quality queries. Not a 5 because that unqualified term creates minor overlap risk with adjacent skills.

4 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

tech-leads-club/agent-skills

Path

packages/skills-catalog/skills/(gtm)/lead-enrichment/SKILL.md

Reviewed

Table of Contents

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