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ad-lead-quality-analyzer

For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

66

Quality

83%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%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.

A tightly written, highly actionable analysis workflow: exact formulas, hard numeric thresholds, a gating validation phase with a fallback mode, and a mandatory report structure, all in third-person imperative voice with explicit output standards and scope exclusions. The only improvements are minor — slight intro redundancy, one vague data-pull instruction, and templates that could be split into reference files.

DimensionReasoningScore

Conciseness

Dense, table-driven content with no tutorial padding — it states its own thesis ("The lowest-CPA campaign is often the one bringing in the *worst* leads") rather than explaining concepts Claude already knows — but the "Core principle" paragraph partially restates the intro and the "When to Use" list duplicates the frontmatter description, so minor trims remain.

4 / 5

Actionability

Concrete executable guidance throughout: exact formulas (True CAC = spend ÷ qualified leads), hard thresholds (≥80%/50–80%/<50% joinable, ≥30 signups, 14-day window), a sample size (10–20 signups), classification rules per bucket, and an exact 7-section report template; the only gap is that pulling Meta-side data ("via the existing Meta Marketing API connection") lacks an example call or query.

4 / 5

Workflow Clarity

Phases 0–6 are clearly sequenced with explicit validation checkpoints and feedback loops: a discovery gate ("Don't proceed until each is answered"), a gating tracking-validation step with coverage thresholds, a hard fallback (<50% joinable → tracking-gap mode, skip Phases 2–6), cohort-maturity guards on Cut decisions, and confidence flags on every recommendation.

5 / 5

Progressive Disclosure

No bundle files exist and the skill is self-contained with clear, well-ordered sections and no buried references; the report and tracking-gap output templates are inlined where they could plausibly live in separate reference files, which is a minor organization gap rather than a structural problem.

4 / 5

Total

17

/

20

Passed

Description

80%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 specific, third-person description that clearly states what the skill does with concrete, comprehensive actions and an explicit target domain. The main gaps are minor: no user-facing "use when" trigger phrasing and a few missing natural synonyms (lead quality, cost per acquisition, Meta ads).

Suggestions

Add an explicit trigger clause, e.g. "Use when the user asks about lead quality, true CAC per qualified lead, or whether to trust Meta's CPA before scaling."

Include common synonyms and platform names users would naturally say — "lead quality", "cost per acquisition", "Meta ads" — to strengthen trigger-term coverage.

The Scale / Keep / Investigate / Cut bucket list is dense; trimming it to "classifies creatives into action buckets" would keep the description lean while the body already defines the buckets.

DimensionReasoningScore

Specificity

Names the domain ("paid lead-gen and participant-recruitment ads") and lists four concrete actions — joining ad-platform data with downstream funnel events, replacing vanity CPA with true CAC per qualified lead, surfacing tracking gaps, and classifying creatives into Scale / Keep / Investigate / Cut — which comprehensively covers the skill's capabilities as described in its body.

5 / 5

Completeness

The "what" is fully explicit (join, compute true CAC, surface gaps, classify) and "when" is present via "For paid lead-gen and participant-recruitment ads", which is explicit scoping rather than a missing trigger — but the when-clause lacks user-facing trigger phrasing ("Use when the user asks…" or equivalent), matching the anchor where 'when' could be more explicit.

4 / 5

Trigger Term Quality

Good coverage of natural terms a practitioner would say ("lead-gen", "CPA", "CAC", "qualified lead", "creatives", "funnel"), but common synonyms and spelled-out forms like "lead quality", "cost per acquisition", or "Meta/Facebook ads" are missing, so it falls just short of the comprehensive-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

The niche (lead-quality CAC analysis for lead-gen/recruitment ads) is distinct with specific triggers, but there is minor overlap risk with closely related ad-analysis skills (e.g. general ad-performance or campaign analyzers) that a user might invoke instead.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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