Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Fixed manifest: declared MEMORIES_API_KEY requirement, documented external API calls and Python dependencies, added privacy note
What This Skill Does
Analyzes video ads from YouTube, TikTok, Instagram Reels, and Twitter using audio transcripts and quantitative thresholds. Compares high and low ROI content by measuring word count, pacing per product, and structure. Generates coaching feedback for creators based on benchmarks derived from high-performing ads.
Gives creators specific numbers to act on, word count and seconds-per-product, instead of subjective opinions, by benchmarking against measured patterns from high-ROI ads.
When to use it
- Diagnosing why a sponsored reel drove few sales despite high views
- Coaching a brand creator on script length and product pacing
- Comparing top-performing and underperforming videos across a paid campaign
- Drafting structured feedback emails to send to influencer partners
- Batch-analyzing an Excel export of campaign ROI data
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Why is this Instagram reel underperforming? https://instagram.com/reel/DRCdjLlDcla
- 1Detects platform from the URL
- 2Sends URL to Memories.ai API to fetch the audio transcript
- 3Counts words and checks against thresholds (under 100 is good, over 150 is bad)
- 4Identifies structural issues such as slow pacing or missing upfront product reveal
- 5Generates creator feedback using the coaching template with specific numbers
Feedback report: 168 words detected (BAD), approximately 30s per product (BAD), recommend showing all products in the first 2-3 seconds and replacing verbal explanations with visual demonstrations
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.