SKILLEMALL.ai

BC IPdesign-3Dprint

End-to-end AI-powered pipeline for creating 3D-printable IP character figurines (Pop Mart style). Three-mode image generation: ComfyUI local (GPU), ComfyUI Cloud, or API-only (Gemini/Imagen/FLUX). Automates Blender modeling with Solidify + Subdivision + color + STL export.

ClawHub Agent Skills author: emergencescience v1.0.0 MIT-0 4 files body ≈ 1 450 tokens Open the sourceclawhub.ai analyzed 30 h ago

End-to-end AI-powered pipeline for creating 3D-printable IP character figurines (Pop Mart style).

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureBlenderDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
98
Quality 40%
53
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 Exfiltration exfil-secret-in-url SKILL.md:69
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (destination is a well-known publishing service; quoted — discussed, not commanded)
    curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/imag…ict?key=…" \
    known servicequoted
  • low Exfiltration net-credential-use SKILL.md:69
    Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)
    curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/imag…ict?key=…" \
    known service

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: End-to-end AI-powered pipeline for creating 3D-printable IP charac… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "title"

Process rating: all ten parameters 61/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1450 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
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 273: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.

External checks

ClawHub: clean
This skill is a disclosed 3D character-to-print workflow that uses optional cloud image generation and local Blender scripts without evidence of hidden exfiltration or persistence.
LLM: benign (high) · VirusTotal: · 30 May 2026