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ad-creative-fatigue-detector

Detect, predict, and resolve ad creative fatigue across platforms. Use when analyzing frequency vs CTR decay, predicting creative lifespan, planning rotation strategies, or calculating statistical significance for A/B tests.

Quality

82%

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Passed

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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.

The body is highly actionable with concrete formulas, worked examples, and decision rules, and the workflows are clearly sequenced with triage checkpoints. Its weaknesses are token efficiency (duplicated framing, textbook statistics, and a promotional footer) and a monolithic structure that inlines reference tables a bundle would offload.

Suggestions

Remove the promotional "About this skill" footer and the Capabilities list that duplicates the section headings, and trim the z-test explanation to just the formulas and interpretation table since the underlying statistics are standard knowledge.

Split the stable reference material — platform fatigue thresholds, decay constants, and refresh/lifespan tables — into files under references/ and link to them from a concise overview section, keeping SKILL.md focused on the detection framework and workflows.

Add a validation step to the workflows (e.g., recompute the fatigue score one week after a swap to confirm the replacement is performing) to close the feedback loop on rotation decisions.

DimensionReasoningScore

Conciseness

The threshold tables and decay constants are novel, token-dense material, but the intro paragraph restates the description, the Capabilities list duplicates the section headers, the standard z-test/sample-size statistics are explained with step-by-step arithmetic Claude already knows, and a promotional footer with UTM tracking links is pure padding. Mostly efficient but needs tightening — not 4, where over-explanation would be only minor.

3 / 5

Actionability

Fully executable guidance throughout: the composite fatigue formula with explicit weights and interpretation bands, the exponential decay model with a worked numeric example, complete two-proportion z-test and sample-size formulas, and a three-tier rotation system with explicit swap triggers. For an instruction-only analytical skill, the worked examples are copy-paste adaptable and cover the common cases.

5 / 5

Workflow Clarity

Three workflows with numbered steps and score-range triage tables that act as decision checkpoints ("0.50+ → Replace immediately", "0.30-0.50 → Prepare replacement"). Not 5 because there are no explicit validation or feedback loops (e.g., re-checking scores after a swap); not 3 since checkpoints are present, just not true verify-then-proceed gates.

4 / 5

Progressive Disclosure

A single ~420-line monolithic file with good section headers but no bundle files at all; the platform threshold tables, refresh strategy reference, and format-lifespan tables are stable reference material that belongs in separate referenced files. Structure is genuinely good (above anchor 2), but content that should be separate is fully inlined with no references — anchor 3.

3 / 5

Total

15

/

20

Passed

Description

83%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 that clearly states what the skill does and when to use it, with concrete domain-specific trigger phrases in third-person voice. Minor improvements possible: name the platforms instead of "across platforms" and add common synonyms like "ad fatigue" or "creative refresh" to widen natural trigger coverage.

DimensionReasoningScore

Specificity

"Detect, predict, and resolve ad creative fatigue" plus concrete sub-tasks ("analyzing frequency vs CTR decay", "predicting creative lifespan", "planning rotation strategies", "calculating statistical significance") lists several specific actions. Not 5 because "across platforms" leaves the platforms unnamed and coverage has minor gaps.

4 / 5

Completeness

Explicitly answers both "what" ("Detect, predict, and resolve ad creative fatigue") and "when" ("Use when analyzing frequency vs CTR decay, predicting creative lifespan, planning rotation strategies, or calculating statistical significance for A/B tests") with concrete trigger phrases in third-person voice.

5 / 5

Trigger Term Quality

Natural media-buyer phrases like "ad creative fatigue", "frequency vs CTR decay", "creative lifespan", and "rotation strategies" are present. Not 5 because common synonyms such as "ad fatigue", "creative refresh", or "banner blindness" are missing.

4 / 5

Distinctiveness Conflict Risk

"Ad creative fatigue" is a clear niche with distinct triggers, but "calculating statistical significance for A/B tests" could overlap with a general A/B-testing or analytics skill. Mostly distinct with minor overlap risk, matching anchor 4.

4 / 5

Total

17

/

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

Synter-Media-AI/free-skills

Path

skills/ad-creative-fatigue-detector/SKILL.md

Reviewed

Table of Contents

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