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BC scroll-world-storytelling

Turn an article, case study, brand narrative, product journey, or long-form story into a cinematic scroll-driven landing page using one of three renderers: scrubbed video, a real-time Three.js world, or semantic HTML/SVG data and typography. Use when the user asks for a scroll world, fly-through landing page, article-to-website transformation, animated planet, data scrollytelling, video-scrubbed page, connected visual journey, or story-led alternative to ordinary stacked sections.

MengTo/Skills Agent Skills author: MengTo MIT 15 files · 2 scripts body ≈ 2 820 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Turn an article, case study, brand narrative, product journey, or long-form story into a cinematic scroll-driven landing page using one of three renderers…

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorMedia and videoMarketingWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
98
Quality 40%
80
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token demo/threejs/assets/three.core.min.js:6
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      const t="182",e={LEFT:0,MIDDLE:1,RIGHT:2,ROTATE:0,DOLLY:1,PAN:2},i={ROTATE:0,PAN:1,DOLLY_PAN:2,DOLL…E:3},s=0,r=1,n=2,a=3,o=0,h=1,l=2,c=3,u=0,d=1,p=2,m=0,y=1,g=2,f=3,x=4,b=5,v=100,w=101,M=102,S=1
      detector
    • low Secrets in code secret-high-entropy-token demo/threejs/assets/three.module.min.js:6
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      import{Matrix3 as e,Vector2 as t,Color as n,mergeUniforms as i,Vector3 as r,CubeUVReflectionMapping as a,Mesh as o,BoxGeometry as s,ShaderMaterial as l,BackSide as c,cloneUniforms as d,Euler as u,Matr
      detector

    Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 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. 6 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 92 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2820 tokens
    • low 11 top-level sections: this looks like several domains in one skill

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 485: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 92 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.