ads-audit

Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform weighting, beta-feature eligibility and scoring, spend audits, tracking audits, or prioritized opportunities and risks.

Quality

98%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

96%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 skill body is a tight, actionable operating contract with a clearly sequenced multi-step workflow and explicit validation/recovery checkpoints. The only soft spot is progressive disclosure: it is entirely self-contained with no bundled reference files despite pointing at external artifacts.

Suggestions

Add bundled reference files (e.g. references/finding-schema.json, references/completeness-rules.md) and link to them from the body so the illustrative JSON fragment and rule tables live one level deep rather than inline.

Make the external dependencies explicit and locally resolvable: either bundle the 'main ads operating contract' and 'repository schema' or document where to find them so the workflow's step 1 and validation step are not left dangling.

Move the per-platform worker manifest (the audit-* list) into a references file with one line per platform's capability pointer, keeping SKILL.md as an overview that signals where detail lives.

Dimension	Reasoning	Score
Conciseness	The body is lean and free of padded concept explanations (no 'what is an ad platform' filler); each section — procedure, worker list, finding schema, completeness rules, weighting, synthesis boundaries, outputs — earns its place and assumes Claude's competence.	5 / 5
Actionability	Provides copy-paste-ready structured guidance: explicit worker names, an illustrative JSON finding schema with exact field names and enums, numeric evidence-coverage thresholds (60-79%, <60%), and a concrete weighting/removal rule, with a pointer to the repository schema for the authoritative version.	5 / 5
Workflow Clarity	An 11-step numbered procedure includes explicit validation checkpoints (step 7 validate against the common finding schema with one retry and failure recording) and a final verify step (step 11: bundle completeness, citations, privacy, render integrity), with feedback loops for the batch/multi-platform operation.	5 / 5
Progressive Disclosure	The body is well organized into clearly headed sections with easy navigation, but it is a single self-contained file with no one-level-deep reference files (the referenced 'repository schema' and 'main ads operating contract' are not present in the bundle), leaving minor organization gaps versus a fully split structure.	4 / 5
	Total	19 / 20 Passed

Description

100%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.

The description is exemplary: third-person voice, a precise what-statement, and an explicit, broad 'Use for...' trigger clause enumerating many concrete scenarios and platforms. Both what and when are answered clearly with low conflict risk.

Dimension	Reasoning	Score
Specificity	Names the domain ('source-grounded paid-advertising audit') and lists multiple concrete actions across platforms plus use cases like 'account health reviews', 'paid-media diagnostics', 'spend audits', and 'tracking audits' — comprehensive coverage rather than just several actions.	5 / 5
Completeness	Explicitly states what ('Run a source-grounded paid-advertising audit for one or more of [platforms]') and when ('Use for full ad checks, account health reviews, ... spend audits, tracking audits, or prioritized opportunities and risks') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural phrases a user would actually say ('full ad checks', 'account health reviews', 'spend audits', 'tracking audits', 'prioritized opportunities and risks') alongside the full platform list, giving comprehensive coverage of relevant trigger terms.	5 / 5
Distinctiveness Conflict Risk	The paid-advertising-audit niche, 'source-grounded' qualifier, and enumerated platform list create a clear, distinct trigger surface with minimal overlap risk against unrelated skills.	5 / 5
	Total	20 / 20 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: AgriciDaniel/claude-ads
Path: skills/ads-audit/SKILL.md
Commit: ac21644

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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