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ads-performance-analytics

How to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution. Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue.

67

Quality

84%

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SKILL.md
Quality
Evals
Security

Quality

Content

71%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 well-structured interpretive playbook with excellent progressive disclosure (verified real, one-level references), a clear decision framework with a defined output, and largely actionable guidance. The main weakness is conciseness: several sections re-teach standard attribution and ROAS/LTV concepts Claude already knows, which could be trimmed in favor of pointers to the reference files.

Suggestions

Compress the six standard attribution-model definitions to a one-line bias note each (or defer to references/attribution-model-comparison.md) since Claude already knows last-click/first-click/linear/time-decay basics.

Trim foundational framing like 'ROAS is short-term... LTV is long-term' and the ROAS-vs-LTV primer to the worked example and the payback-period decision rule, which carry the actual guidance.

Consolidate the scattered detection thresholds and pre-commitment rules (test-duration, analysis-window, 30% divergence) into the 12-considerations framework as explicit validation gates so the Scale/Hold/Kill output has a single checkable procedure.

DimensionReasoningScore

Conciseness

The body is mostly tight and every section carries domain-specific judgment (incrementality rate ranges, platform-specific conversion-window defaults, detection thresholds like 'platform-reported exceeds warehouse-attributed by more than 30%'), but several stretches re-explain concepts Claude already knows — e.g., textbook definitions of last-click ('The conversion is fully credited to the last click before the conversion event'), first-click, linear, and time-decay attribution models, and basics like 'ROAS is short-term... LTV is long-term.' The attribution-model section in particular duplicates material that could be compressed to a pointer into references/attribution-model-comparison.md.

3 / 5

Actionability

As an instruction-only skill it gives concrete, executable guidance: an explicit blended CAC formula ('(total ad spend across platforms) divided by (total new customers from warehouse)'), worked numeric examples (Meta 2.5x ROAS / $80 LTV vs Google 1.8x / $200 LTV), concrete thresholds ('real performance changes are 30% or more'), a 12-item checklist, and a defined three-way decision output (Scale / Hold / Kill). Minor gaps: no concrete reconciliation commands or example dashboard queries, and some guidance stays at the principle level ('run incrementality tests at least quarterly') without setup specifics deferred to references.

4 / 5

Workflow Clarity

The '12 considerations' section gives an explicit ordered walk-through with a defined terminal decision (Scale/Hold/Kill), and earlier sections sequence the material logically (panel completeness → reporting quirks → attribution → reconciliation → decision rules). Validation checkpoints exist in the form of explicit detection patterns (platform-vs-warehouse divergence >30%, sum-of-platforms vs warehouse totals) and a pre-committed data-gap rule. It falls short of a 5 because checkpoints are embedded across sections rather than consolidated into the decision procedure, and the pre-commitment rules (test windows, analysis windows) are described but not wired into the framework as explicit gates.

4 / 5

Progressive Disclosure

The body is a genuine overview with detail correctly pushed to seven real one-level-deep reference files; all referenced paths (attribution-model-comparison.md, platform-reporting-quirks.md, dashboard-reconciliation-patterns.md, cohort-analysis-templates.md, incrementality-testing-playbook.md, common-interpretation-failures.md, metric-definitions-glossary.md) exist in references/ and contain the promised content. Each is signaled inline at the relevant section with a clear one-line description of what it holds, plus a consolidated Reference files section. Navigation is easy and nothing is nested two levels deep.

5 / 5

Total

16

/

20

Passed

Description

91%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 with explicit what-and-when structure and an unusually rich, natural set of trigger terms including behavioral triggers. The main gaps are that capabilities are stated as topic areas rather than concrete actions, and no explicit boundary against adjacent marketing skills is drawn.

Suggestions

Convert one or two topic areas into concrete actions (e.g., 'reconcile platform-reported conversions against warehouse data' instead of just naming 'multi-platform reconciliation').

Add a brief boundary clause (e.g., 'for campaign strategy or creative, use paid-media-strategy / ads-creative-development') to reduce overlap with sibling marketing skills.

DimensionReasoningScore

Specificity

The description enumerates many concrete capability areas — "Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing" — under the action "read paid media dashboards without fooling yourself." These are topic domains rather than discrete executable actions (compare "Extract text and tables from PDF files, fill forms, merge documents"), so it lists several specific items with minor gaps rather than fully comprehensive coverage of actions; it is clearly above the '1-2 concrete actions' anchor.

4 / 5

Completeness

It explicitly answers both questions: what ("How to read paid media dashboards without fooling yourself" plus the enumerated capability areas) and when ("Triggers on [list]... Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue"). Both are concrete and explicit, matching the anchor for a clear what-and-when with concrete trigger phrases.

5 / 5

Trigger Term Quality

Trigger coverage is comprehensive and natural: "read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution," plus behavioral triggers ("about to scale, kill, or rebudget a campaign based on platform metrics"). It includes synonyms, acronyms, and phrases a marketer would actually say.

5 / 5

Distinctiveness Conflict Risk

The niche is clear — interpretation of paid media reporting rather than strategy or creative — and triggers like "geo holdout," "blended CAC," and "reconciling platform reports against warehouse revenue" are distinctive. However, the description does not explicitly delineate the boundary against closely related skills (the body notes paid-media-strategy and ads-creative-development as siblings), and terms like "attribution analysis" or "MMM" have some overlap with general analytics skills, leaving minor conflict risk.

4 / 5

Total

18

/

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

rampstackco/claude-skills

Path

skills/ads-performance-analytics/SKILL.md

Reviewed

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