Multi-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, and Amazon Ads. 250+ checks with scoring, parallel agents, industry templates, AI creative generation, attribution and server-side tracking deep dives.

Quality

76%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./ads/SKILL.md

Quality

Discovery

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong description with excellent specificity and trigger term coverage across multiple advertising platforms. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know precisely when to select this skill. The description is distinctive and unlikely to be confused with other skills.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks to audit, review, or optimize paid advertising campaigns, or mentions ad spend, ROAS, ad performance, or any of the supported ad platforms.'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'audit and optimization', 'analyzes' specific platforms, '250+ checks with scoring', 'parallel agents', 'industry templates', 'AI creative generation', 'attribution and server-side tracking deep dives'. These are concrete, specific capabilities.	3 / 3
Completeness	The 'what' is well-covered with specific platforms and capabilities, but there is no explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied by the nature of the capabilities described, which per the rubric caps completeness at 2.	2 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'Google Ads', 'Meta', 'YouTube', 'LinkedIn', 'TikTok', 'Microsoft', 'Apple', 'Amazon Ads', 'paid advertising', 'audit', 'optimization', 'attribution', 'creative generation'. These are terms users naturally use when seeking ad platform help.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive with a clear niche: multi-platform paid advertising audit and optimization. The specific platform names (Google, Meta, TikTok, etc.) and domain-specific terms (attribution, server-side tracking, ad creative) make it very unlikely to conflict with other skills.	3 / 3
	Total	11 / 12 Passed

Implementation

70%

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

This is a well-structured orchestration skill with strong workflow clarity and excellent progressive disclosure across a large number of sub-skills and reference files. Its main weaknesses are moderate verbosity (duplicated information between the command table and sub-skills list, overly detailed footer rules) and a lack of concrete executable examples or output schemas that would make the guidance more actionable. The quality gates and industry detection sections are genuinely useful and non-obvious.

Suggestions

Add a concrete example of expected subagent JSON output schema so the validation step in orchestration is fully actionable rather than abstract.

Remove or consolidate the numbered Sub-Skills list (items 1-22) since it largely duplicates the Quick Reference command table — or merge them into a single table with sub-skill name, command, and description.

Add a brief example of a scored audit output (even a truncated one) showing the Ads Health Score calculation with real-looking numbers to make the scoring methodology concrete.

Trim the Community Footer section — the show/skip lists could be replaced with a single rule like 'Show after any major deliverable command; skip after utilities, intermediate steps, and prompts.'

Dimension	Reasoning	Score
Conciseness	The skill is quite long (~250 lines) and includes some content that could be trimmed — the full sub-skills enumeration largely duplicates the command table, the community footer section is verbose with explicit show/skip lists, and the 10-Principle Thinking Framework section is vague filler. However, most sections (Quality Gates, Industry Detection, Scoring) carry useful, non-obvious information.	2 / 3
Actionability	The skill provides concrete quality gates, specific thresholds (3x Kill Rule, budget sufficiency formulas), and clear command mappings. However, there is no executable code, no example audit output, no sample JSON schema for subagent results, and the orchestration logic describes steps abstractly rather than showing concrete tool invocations or data formats.	2 / 3
Workflow Clarity	The orchestration logic has a clear numbered sequence with an explicit validation step (step 5: verify subagent JSON before aggregating). The creative workflow is a well-sequenced pipeline with clear inputs/outputs per step. The PDF report quality gate includes a validate-then-proceed pattern. Context intake is explicitly marked as 'always do this first'.	3 / 3
Progressive Disclosure	The skill is structured as a clear overview with a well-organized reference file listing (25+ files) with explicit paths and descriptions. Content is appropriately split between the main SKILL.md (orchestration, quality gates, scoring) and referenced sub-skills/reference files. Navigation is one level deep and clearly signaled.	3 / 3
	Total	10 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: AgriciDaniel/claude-ads
Commit: 283d9d4

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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