BB UGC Fashion & Activewear Product Video Generator — Fitness Ecommerce Content Creator for Social Media Influencers on Tik
UGC video generator for fashion and activewear brands. Turns a single outfit image into TikTok and Instagram Reels ready product videos — talking head and voiceover styles. Built for fitness fashion, athleisure, and activewear product marketing. Generates social-native UGC content with consistent model, outfit, and styling across every shot. Product video generator for ecommerce, DTC brands, and social commerce campaigns. Fashion video generator creating influencer-style try-on and lifestyle content.
As a process B 70/100 · Nearly there — weak spots: result and completion, consistency, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
name-longname is longer than 64 chars - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "keywords" - note
frontmatter-keyunknown frontmatter key "requires"
Process rating: all ten parameters 70/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (UGC Fashion & Activewear Product Video Generator — Fitness Ecommerce Content Creator for Social Media Influencers on TikTok, Instagram Reels) differs from the folder (ugc-fashion-activewear-product-video-generator)
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 33 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Execution cost. Instruction body is 1368 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 505: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.