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

96%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

92%Weight 40%Scale 1-3

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

The body is lean, highly actionable, and workflow-clear with strong validation feedback loops for a batch operation. Its main weakness is monolithic single-file organization with references to bundle materials that are not actually present.

Suggestions

Move the finding-field JSON schema and/or completeness rules into a referenced reference file (e.g. FINDINGS.md) so SKILL.md stays an overview pointing one level deep.

Verify the referenced external materials (the `ads` operating contract, platform capability manifests, the repository schema) actually exist in the bundle, or note where they live so the references are not dangling.

Consider splitting per-platform worker detail into a separate platforms reference to reduce the inline worker list and completeness spec.

Dimension	Reasoning	Score
Conciseness	The body is dense procedural instruction that assumes competence ("Do not calculate or repair scores in the prompt", "Never substitute feature awareness for account health") without explaining basic ad concepts, so every token earns its place.	3 / 3
Actionability	Provides concrete, specific guidance: named worker lists, a complete JSON finding schema with enumerated field values, exact output filenames, and numeric thresholds (60%, 79% coverage), all actionable rather than abstract.	3 / 3
Workflow Clarity	An explicit 11-step procedure with validation checkpoints (step 7 validates against the common finding schema with one-retry feedback, step 11 verifies bundle completeness) and clear error-recovery handling for a batch operation.	3 / 3
Progressive Disclosure	Sections are clearly organized, but the skill is a single ~145-line monolithic file with substantial inline detail (JSON schema, completeness rules, synthesis boundaries) and references to external materials ("the main `ads` operating contract", "the repository schema", platform manifests) that have no corresponding bundle files present.	2 / 3
	Total	11 / 12 Passed

Description

100%Weight 40%Scale 1-3

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 specific, third-person, and complete, covering both capabilities and explicit use triggers across a clearly bounded paid-advertising niche. It avoids fluff and verbosity while remaining comprehensive.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ("source-grounded paid-advertising audit", "account health reviews", "paid-media diagnostics", "spend audits", "tracking audits") across twelve explicitly named platforms, matching the level-3 anchor for multiple specific concrete actions.	3 / 3
Completeness	Explicitly answers both what ("Run a source-grounded paid-advertising audit...") and when ("Use for full ad checks...") with an explicit trigger clause, satisfying the level-3 anchor for both what AND when.	3 / 3
Trigger Term Quality	Uses natural user-facing terms ("full ad checks", "account health reviews", "spend audits", "tracking audits", "prioritized opportunities and risks") that a user would plausibly say, with broad coverage; not merely technical jargon.	3 / 3
Distinctiveness Conflict Risk	The paid-advertising audit niche and enumerated platforms make it clearly distinguishable from other skills with distinct triggers; unlikely to fire for unrelated skills.	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: AgriciDaniel/claude-ads
Path: skills/ads-audit/SKILL.md
Commit: 669c760

Reviewed: 17 days ago

Table of Contents

Discovery Implementation Validation

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