ad-creative

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

Quality

88%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

77%

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, highly actionable skill that provides concrete guidance for ad creative generation across multiple platforms. Its main weakness is verbosity — it includes platform spec tables that are also referenced in an external file, explains copywriting fundamentals Claude already knows, and could be more aggressively trimmed. The workflow clarity is excellent with clear sequencing, validation steps, and iteration loops.

Suggestions

Move the detailed platform specs tables entirely to references/platform-specs.md and keep only a brief summary or the most critical limits inline, since the reference file is already cited.

Remove or significantly trim the 'Writing Quality Standards' section — Claude already knows copywriting fundamentals like active voice, specificity, and avoiding jargon. Keep only project-specific standards or unusual constraints.

Ensure the referenced bundle files (references/platform-specs.md, references/generative-tools.md) actually exist in the bundle to support the progressive disclosure structure.

Dimension	Reasoning	Score
Conciseness	The skill is quite long (~300+ lines) and includes some content Claude already knows (e.g., explaining what RSAs are, basic copywriting principles like 'active voice over passive'). The platform specs tables are useful reference material but could be offloaded to the referenced platform-specs.md file. The 'Writing Quality Standards' section largely restates copywriting fundamentals Claude already understands.	2 / 3
Actionability	The skill provides highly concrete, actionable guidance: specific character limits per platform in table format, structured output format examples with character counts, CSV templates for bulk upload, iteration log templates, and specific bash commands for pulling performance data. The step-by-step workflows for both generation and iteration are clear and executable.	3 / 3
Workflow Clarity	Multi-step workflows are clearly sequenced with explicit validation checkpoints. The generate flow (Define Angles → Generate Variations → Validate Against Specs → Organize for Upload) includes a validation step before delivery. The iteration flow has clear analysis steps before generation. The batch generation workflow includes a quality filter step. The core loop is explicitly stated.	3 / 3
Progressive Disclosure	The skill references external files like 'references/platform-specs.md' and 'references/generative-tools.md' which is good progressive disclosure design, but no bundle files were provided to verify these exist. The main SKILL.md itself is quite long and includes detailed platform specs tables that it simultaneously says are covered in the referenced file, creating redundancy. The related skills section provides good navigation but the body content could benefit from more aggressive offloading.	2 / 3
	Total	10 / 12 Passed

Description

100%

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 skill description that clearly defines its scope (paid ad creative), lists specific platforms and deliverables, and includes an explicit 'Use when' clause with natural trigger terms. It uses proper third-person voice and is concise without being vague. It serves as a near-ideal example of a well-crafted skill description.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'create, iterate, and scale paid ad creative', 'generating headlines, descriptions, primary text', and 'large sets of ad variations for testing and performance optimization'. These are concrete, actionable capabilities.	3 / 3
Completeness	Clearly answers both 'what' (create, iterate, and scale paid ad creative for multiple platforms) and 'when' (explicit 'Use when' clause covering generating headlines, descriptions, primary text, or ad variations for testing).	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'Google Ads', 'Meta', 'LinkedIn', 'TikTok', 'headlines', 'descriptions', 'primary text', 'ad variations', 'ad creative', 'paid ad'. These are all terms users would naturally use when requesting ad copy help.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive with a clear niche in paid advertising creative across specific platforms. The mention of specific platforms (Google Ads, Meta, LinkedIn, TikTok) and ad-specific terms (headlines, primary text, ad variations) make it unlikely to conflict with general copywriting or marketing strategy skills.	3 / 3
	Total	12 / 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: sickn33/antigravity-awesome-skills
Commit: c59011f

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

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