AD cad-viewer
Start or reuse CAD Viewer and return review links for explicit CAD, implicit CAD, robot-description, and G-code files. Use when visually reviewing `.step`, `.stp`, `.implicit.js`, `.implicit.mjs`, `.glb`, `.stl`, `.3mf`, `.gcode`, `.dxf`, `.urdf`, `.srdf`, or `.sdf` files, especially when handed off from CAD, implicit-cad, G-code, URDF, SRDF, or SDF generation skills.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Secrets in code
secret-high-entropy-tokenscripts/viewer/dist/assets/GLTFLoader-B3ztFMBW.js:1High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)import{TrianglesDrawMode as Re,TriangleFanDrawMode as W,TriangleStripDrawMode as ce,Loader as xe,LoaderUtils as H,FileLoader as le,MeshPhysicalMaterial as M,Vector2 as ue,Color as O,LinearSRGBColorSpadetector -
low Secrets in code
secret-high-entropy-tokenscripts/viewer/packages/cadjs/src/lib/render/glbMeshData.js:115High-entropy token-like string (may be an id, hash or a credential)function isBu…rix(matrix) { -
low Secrets in code
secret-high-entropy-tokenscripts/viewer/packages/cadjs/src/lib/render/glbMeshData.js:132High-entropy token-like string (may be an id, hash or a credential)if (children.length !== 1 || !isBu…rix(children[0]?.matrixWorld)) {
Files scanned: 80. 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 49/100
- 0Result and completion. Does not say what the result is
- 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
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1049 tokens
- low The response is described with custom markup (3 tags): a typed call is more reliable
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
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 370: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.