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

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Quality

Content

77%

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

A thorough, highly actionable enrichment reference with clear sequenced workflows and validation checkpoints. Its main weaknesses are conciseness (dated inline pricing tables and re-explained concepts) and under-used progressive disclosure that leaves the bulk of detail in the main body.

Suggestions

Move dated, volatile data like 'Clay Pricing (2026)' and the full provider comparison matrix into references/ and keep the body to stable decision guidance, noting that pricing is time-sensitive.

Trim conceptual restatements Claude already knows (e.g., the opening definition of a waterfall) and keep only the novel sequencing/threshold detail.

Expand references/quick-reference.md (or add a second reference) to absorb the dense scoring tables so the SKILL.md body reads as a lean overview with well-signaled one-level-deep references.

Dimension	Reasoning	Score
Conciseness	The ~450-line body is mostly efficient and rich with genuinely novel provider/pricing data, but it re-explains concepts Claude knows ('A waterfall enrichment system queries multiple data providers in sequence...') and inlines dated 'Clay Pricing (2026)' tables that could be tightened or moved to a reference.	2 / 3
Actionability	Highly concrete and copy-paste ready: an ICP scoring formula, exact firmographic ranges, a labeled waterfall flow, provider selection matrices, a sample Clay table structure (Col A-O with formulas), and an ROI calc framework.	3 / 3
Workflow Clarity	Multi-step processes are clearly sequenced with explicit validation checkpoints (confidence >0.85, bounce <2%, credit alert at 75%) and checklists (Deliverability Protection Checklist, Credit Governance Rules) for batch/reputation-sensitive operations.	3 / 3
Progressive Disclosure	It signals one real one-level reference (`references/quick-reference.md`, which exists), but the dense pricing/scoring tables are inlined in the body while the reference file is comparatively thin — content that should be split is inline.	2 / 3
	Total	10 / 12 Passed

Description

100%

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, specific description that names concrete actions, includes natural trigger terms and tool names, and covers both what and when with a helpful negative-scope boundary. It is a model example of a well-constructed skill description.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality') rather than vague language.	3 / 3
Completeness	Explicitly answers both what (waterfalls, ICP scoring, contact verification) and when ('When the user wants to...' / 'Also use when the user mentions...'), with explicit triggers and a negative-scope clause.	3 / 3
Trigger Term Quality	Strong coverage of natural user terms including tool names ('enrichment,' 'Clay,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'Apollo,' 'ZoomInfo') matching the high-anchor example.	3 / 3
Distinctiveness Conflict Risk	Clear B2B-enrichment niche with tool-specific triggers and an explicit exclusion ('Do NOT use for technical implementation, code review, or software architecture'), making conflicts unlikely.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

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
Commit: 9026164

Reviewed: 4 days ago

Table of Contents

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