agentsclimarketplace

Bodyfit ready check

Skill wjlgatech/design-anything/skills/bodyfit-ready-check

Any design intent in (text, picture) → execution-ready 3D blueprint out — construction- and 3D-print-verified. Game design · simulation · architecture (3DCP+AI) · interior · landscape.

Install
npx -y skills add wjlgatech/design-anything --skill bodyfit-ready-check

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

3 things to look at

  • 18 days oldThe repository was created 18 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Run the body-fit gate on a fit spec (product dimensions for a specific body): completeness, anthropometric/ISO ranges, frame-PD optical alignment, print floor — eyewear first; dental/prosthetics/footwear share the pattern. Trigger: "do these glasses fit", "check this fit spec", "frame for a 63 PD". NOT a fitting: face scan, angles, and Rx compatibility are the optician's.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

1.8 KB, as published. Nobody here has run it

bodyfit-ready-check

When to use

Any body-fit product spec claiming to fit a declared body — before geometry is generated or printed.

What it does

  1. B1 completeness: every data/bodyfit.yml dimension declared — undeclared is not measured ⇒ fail.
  2. B2 ranges: each dimension inside its anthropometric/ISO-lineage range.
  3. B3 alignment: frame PD (lens_w + bridge) within the decentration budget of the wearer's PD — the dispensing rule as a number.
  4. B4 print floor: declared min feature ≥ the product's snap threshold; the geometry itself is then gated by print-ready-check on the STL.

Example

python3 examples/eyewear/generate.py fitspec.json temple.stl
python3 pipeline/bodyfit_gate.py fitspec.json --json
python3 pipeline/ready_gate.py temple.stl --min-feature 3.0

Verification (eval-with-teeth)

Success may be declared ONLY when both gates exit 0. Held by tests that mutate the golden spec five known-bad ways (missing dim, out-of-range PD, misaligned frame, thin feature, unknown product) and assert each fails:

python3 -m pytest tests/test_m8_m11_m9.py -q

Safety

Table-fit, not fitted: population ranges say a spec is plausible, not that it fits one specific face. The report says so.

Cross-runtime

Python + PyYAML; exit codes gate any CI.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.