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BD crayon-storybook

Make warm children's picture-book animations (MP4) drawn in crayon, coloured pencil and pastel on cream drawing paper — waxy crayon scribble fills broken by paper tooth, coloured-pencil outlines, slow 8 fps line boil, page-turn transitions, picture-book page framing and hand-lettered CJK storybook captions. p5.js + p5.brush rendered frame by frame in headless Chrome, encoded with ffmpeg. Use when a reference video or brief calls for a crayon / colored-pencil / pastel / kids' drawing / picture-book / bedtime-story / 繪本 / 蠟筆 / 色鉛筆 / 童書 look, or when the video-clone router picks the crayon-storybook style.

edenfunf/reelmimic Agent Skills author: edenfunf 18 files · 11 scripts body ≈ 1 537 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Make warm children's picture-book animations (MP4) drawn in crayon, coloured pencil and pastel on cream drawing paper — waxy crayon scribble fills broken by…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorMedia and videotype 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
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
87
Run on models
none yet
Process rating
D
44/100
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 template/package-lock.json:29
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…lnb+xqDemAMmWQB+8Q0b+8VEq…E8Q==",
      detector
    • low Secrets in code secret-high-entropy-token template/package-lock.json:142
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…eBL+/1tqG…AR5+magt…Y4Q+w==",
      detector
    • low Secrets in code secret-high-entropy-token template/package-lock.json:183
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…kSb+UKYd…IJ4+lp54i/hhCl…p7i+22QhNU0+/qk8g==",
      detector
    • low Secrets in code secret-high-entropy-token template/package-lock.json:283
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…zlG+KArF…Uwh/RtOQ…xZg==",
      detector
    • low Secrets in code secret-high-entropy-token template/package-lock.json:301
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…gcz+1ajP…Ps6+giOQ…Fkh+CKow/bkB7…DSw==",
      detector

    Files scanned: 17. 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 44/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 85Steps. 19 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1537 tokens
    • 100Running it twice. No mutating operations

    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 610: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (1 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.