AD smyx-pet-litter-box-waste-analysis
Triggers when a user provides a cat litter box area video URL or file for analysis; supports local video uploads or network URLs to call server-side APIs for waste characteristic recognition, analyzing feces morphology (loose stool, bloody stool, dry hard stool) and urine clump size to identify urinary and digestive system abnormalities, outputting health risk alerts (without diagnosing diseases). Application scenarios: smart litter boxes, multi-cat household health monitoring. Development reason: early signs of urinary diseases, a pain point for multi-cat households. | 当用户提供猫砂盆区域的视频URL或文件时，触发本技能进行排泄物性状分析；支持通过上传本地视频或网络视频URL，调用服务端API进行排泄物识别，分析粪便形态（稀便、血便、干硬便）和尿团大小，识别泌尿系统与消化系统异常，输出健康风险提示（不诊断疾病）。应用场景：智能猫砂盆、多猫家庭健康监测。
As a process D 41/100 · Unfinished process — weak spots: steps, result and completion, 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 · 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 41/100
- 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
- 25Steps. 1 steps
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1130 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -254 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 721: 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.