ad-creative-analysis
Analyze ad creatives (images and videos) extracted from competitor research. Use when given a directory of ad images, video files, or transcripts to evaluate ad quality, score visual and messaging effectiveness, assign a scale score for viral/engagement potential, and generate a cross-creative pattern summary. Triggered by requests like "analyze these ads", "score these creatives", "what hooks are competitors using", "evaluate the ad library", "give me a scale score", "analyze the ad folder", or "what's working in these ads".
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/baitoxkevin/ad-creative-analysisWhat This Skill Does
The Ad Creative Analysis skill is an advanced diagnostic engine designed for performance marketers, creative strategists, and growth teams. It processes raw creative assets—including static images and video files—from your competitor research folders or internal ad libraries. By utilizing deep-vision analysis, the skill evaluates the fundamental building blocks of high-converting ads. For static imagery, it critiques visual hierarchy, color usage, typography, and CTA prominence to ensure your creative stops the scroll. For video content, it analyzes pacing, script structure, and hook efficiency during the critical first three seconds. The skill outputs structured data, enabling you to identify which emotional appeals (e.g., urgency, social proof, aspiration) and hook strategies are currently driving market interest.
Installation
You can integrate this capability into your OpenClaw environment by running the following command in your terminal:
clawhub install openclaw/skills/skills/baitoxkevin/ad-creative-analysis
Use Cases
- Competitor Benchmarking: Rapidly synthesize hundreds of competitor ads to map out their messaging strategy and visual trends.
- A/B Testing Support: Evaluate your existing creative library before launch to predict which variants have the highest viral potential.
- Creative Optimization: Identify why specific campaigns are underperforming by analyzing design dimensions like CTA readability and visual focal points.
- Trend Forecasting: Summarize recurring creative patterns across a dataset to decide on your next creative brief.
Example Prompts
- "Analyze the ads in the /competitor-research/q3-campaigns folder. Tell me which hooks are performing best and provide a scale score for each."
- "I'm uploading 10 video creatives to this folder. Please evaluate the hook quality of each and summarize the common messaging patterns."
- "Evaluate the ad library in the current directory. Identify which visuals have the highest attention-grabbing potential and suggest improvements for the CTA placement."
Tips & Limitations
To get the best results, ensure your image files are high-resolution and that you include a metadata.json file containing performance metrics like spend and impressions. This context allows the skill to correlate visual quality with real-world effectiveness. Note that this skill requires read access to your local filesystem. Avoid including irrelevant files in the target directory to ensure the model focuses purely on creative assets. Always cross-reference the generated 'scale score' with your actual platform data for final budget allocation decisions.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-baitoxkevin-ad-creative-analysis": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read