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Create deterministic hand-drawn, whiteboard, educational, and explainer MP4 animations from a JSON Animation DSL. Use when a user asks to make or edit a hand-drawn video, whiteboard animation, animated SVG explainer, or programmatic animation video.

ClawHub Agent Skills author: ToBeWin v1.0.1 MIT-0 39 files · 3 scripts body ≈ 466 tokens Open the sourceclawhub.ai↗ analyzed 25 h ago

Create deterministic hand-drawn, whiteboard, educational, and explainer MP4 animations from a JSON Animation DSL.

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
82
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:20
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…IJ5+F21M…aFJ/0dsi…lOA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:99
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…S4F+im88…HRE/cYlx…2oE/ufM0p61IKng==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:147
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…rdY+ziCYCPMmtZjjIwOmXFjmyzEHn+UUxk5of+SYsj…5hY/rOAw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:227
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…NmN+loZK…eAz+famM…vZz+zT1jlh/keC3Rj/lg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:656
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…GbH+mKmC…rsg==",
      detector

    Files scanned: 38. 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 47/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 100Steps. 18 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 466 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
    • +4No input/output examples
    • -33 of 5 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 249: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 18 items
    • +4Reference files are cited in the instructions (1 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill has a clear video-rendering purpose, but it should be reviewed because it renders unsanitized SVG/HTML content and can send narration text to an external TTS service.
    LLM: suspicious (high) · VirusTotal: · 26 Aug 2026