THE CRIT

Every image gets a critique.
Not a score.

The Crit reads composition the way an artist does — mass, void, drift, radial gravity, tonal architecture — and tells you what your image is structurally doing, in plain language.

RUNS ENTIRELY IN YOUR BROWSER · YOUR IMAGE NEVER LEAVES YOUR MACHINE

Drop an image here
or click to choose · or paste from clipboard · JPG / PNG / WEBP
no image handy? try a structure:

It measures mass, not subject.

Most image analysis asks what is pictured. The Crit asks how the picture is built. It comes from the Visual Thinking Lens (VTL) — a measurement framework developed by drawing from the masters and then testing generative models against the same geometry.

01 — LOCATE THE MASS

Material mask & mass map

Edges and tonal weight become a mass field — the same thing your eye weighs before it ever names a subject. From it: placement drift, void ratio, cohesion, dispersion, peripheral pull, orientation.

02 — TEST THE GRAVITY

Radial compliance & the default basin

Does the mass organize around its own center or the frame's? Generators settle into a known attractor: centered, radially even, frame-obedient. The Default Gravity Index says how deep in that basin your image sits.

03 — SAY IT PLAINLY

A critique, not a number

The readout becomes paragraphs: what the image is structurally doing, what its loudest decision is, what it's giving up, and two or three concrete things to try. Honest, specific, teachable.

Two ways in.

The same instrument serves two audiences: people who make images, and people who make image-makers.

FOR ARTISTS, PHOTOGRAPHERS, ILLUSTRATORS

A studio crit on demand.

Portfolio reviews cost $50–200. The Crit gives you the structural half of that conversation any time — where your mass sits, what your voids are doing, whether your composition is a choice or a default.

  • Unlimited local analysis, free — nothing is uploaded
  • Deep Crit: the full written review, with your own API key
  • Compare your work against the masters' compositional range
RUN YOUR FIRST CRIT ↑
FOR GEN-AI TEAMS & MODEL LABS

Your model has a compositional fingerprint. We can read it.

Semantic evals miss a whole defect class: compositional monoculture. Diffusion doesn't compose — it settles. The VTL kernel measures where your model settles: centered mass, dead voids, frame-locked radial structure, collapsed orientation.

  • Batch audits: Default Gravity distribution across your output corpus
  • Model-vs-model compositional fingerprint comparison
  • Deterministic, training-data-agnostic, model-internals-agnostic
REQUEST A MODEL AUDIT →