BC HyperFrames
One-off semantic animations and animated explainers authored as HTML + GSAP on HyperFrames, directed by the meaning layer (MeaningMap then Direction, reviewed before anything animates) and rendered to MP4 through the sandboxed HyperFrames seam, with the ArtDirection quality loop before delivery. USE WHEN animation, animate this, motion graphics, animated explainer, content to video, make a short, generate a video about, launch video, product launch video, launch film, capability video, feature video, make a video of what we just added, promo video, ad creative video, landing-page hero video, AI video, video overlay, render video, programmatic video, hyperframes, remotion (retired). NOT FOR static images or diagrams, or animated technical diagram GIFs (Art TechnicalDiagrams, which renders through this seam), editing or tight-cutting recorded footage (the video pipeline skill), narrated essays or explainers of a post, idea or feature (the video-essay skill), or audio-only cleaning (AudioEditor).
One-off semantic animations and animated explainers authored as HTML + GSAP on HyperFrames, directed by the meaning layer (MeaningMap then Direction, reviewed…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 18. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "evals"
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2995 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (8 tags): a typed call is more reliable
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
- +3Description length 1008: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +4Structure: 7 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.