SKILLEMALL.ai

AC high-precision-3d-web-optimize

Optimize high-precision .glb/.gltf models for Web 3D and digital twin delivery. Use when preparing Three.js or Babylon.js assets that need UV-safe simplification, slot-based texture compression (Normal/ORM → UASTC, BaseColor/Emissive → ETC1S), differentiated LOD × slot resolution, Draco compression, LOD generation, manifest outputs, and browser-friendly loading performance without breaking UVs, materials, or texture appearance. Avoid destructive remesh or re-topology unless the user explicitly requests editable low-poly assets.

ClawHub Agent Skills author: Zavon v1.2.0 MIT-0 5 files body ≈ 1 738 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 57/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 0

    ✓ No critical or high findings

    Files scanned: 5. 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 57/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 54 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1738 tokens
    • 100Running it twice. No mutating operations
    • low 12 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 533: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 54 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

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

    External checks

    ClawHub: clean
    This skill is a disclosed local 3D model optimization helper with no evidence of hidden data access, persistence, or harmful behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026