AF smyx-neonatal-jaundice-screening-analysis
Using a neonatal monitor or baby camera, the system captures high-resolution facial images of the newborn and uses AI visual analysis to detect sclera color (white in normal babies, yellow when jaundiced) and facial skin yellowness index (based on skin-color chromatic spaces, e.g., mapping the skin region to estimated clinical bilirubin levels). It outputs a jaundice-risk hint (low / medium / high risk). | 通过新生儿监护器或婴儿摄像头拍摄新生儿面部高清图像，利用AI视觉分析技术检测巩膜（眼白）的颜色（正常白色，黄疸时呈黄色）以及面部皮肤的黄染指数（基于肤色色度空间，如将皮肤区域映射到临床胆红素水平估算），输出黄疸风险提示（低风险/中风险/高风险）。该技能可辅助家长及医护人员早期发现新生儿高胆红素血症，及时就医干预。
Using a neonatal monitor or baby camera, the system captures high-resolution facial images of the newborn and uses AI visual analysis to detect sclera color…
As a process F 32/100 · Will not run — weak spots: steps, result and completion, when it triggers
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 · 0
✓ No critical or high findings
Files scanned: 30. 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 32/100
- 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
- 20When it triggers. No condition that starts the skill
- 25Steps. 1 steps
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1663 tokens
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -257 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 567: enough signal without eating the budget
- +4Structure: 19 headings
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.