BD 3d-underwater-god-rays
Add volumetric underwater god rays to a Three.js scene, marching one drifting swell field along every view ray at half resolution so the light shafts converge on the sun, parallax with the camera and carry rippling caustic streaks, with a shimmering surface underside, a sun that wobbles through the ripples, and the same light dappling fish as they swim through the beams. Use for underwater scenes, oceans seen from below, aquariums, reefs, kelp forests, diving and shipwreck scenes, schools of fish, sunbeams or light shafts through water, caustics, "rays of light shining through the ocean", or watery ripples on a background. Includes a reusable module and the Blue Hour sardine-school demo.
Add volumetric underwater god rays to a Three.js scene, marching one drifting swell field along every view ray at half resolution so the light shafts converge…
As a process D 41/100 · Unfinished process — References files that are not bundled: demo/index.html
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: demo/index.html
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: demo/index.html
- 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
- 70When it triggers. States when to use, but not when not to
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2294 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 696: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.