AD smyx-litter-box-usage-monitor-analysis
Triggers when a user provides a litter-box area video URL or file for analysis; uses object detection and tracking to identify each cat's entry/exit times at the litter box, records daily usage frequency and per-visit duration (entry → exit), and compares against the historical baseline. When frequency rises/falls significantly, or per-visit duration is abnormally long/short, outputs a urinary-disease (cystitis, urinary obstruction, kidney disease) early-warning alert. Especially useful for individualized health management in multi-cat households. Application: multi-cat homes, catteries, vet hospital inpatient wards, boarding centers. Does NOT provide medical diagnosis — only outputs behavior-statistics-based alerts. | 当用户提供猫砂盆区域视频URL或文件时，触发本技能进行使用频次与时长分析；通过智能猫砂盆或固定摄像头分析视频，利用目标检测和跟踪技术识别每只猫咪进出猫砂盆的时刻，记录每日使用频次、单次停留时长（从进入至离开），并与历史基线对比；若频次显著增减或单次时长异常，则输出泌尿系统疾病（膀胱炎、尿闭、肾病等）预警，有助于多猫家庭的个体化管理及早发现健康问题。应用场景：多猫家庭、猫舍、宠物医院住院部、宠物寄养中心。仅输出基于行为统计的提示，不提供医疗诊断。
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 1436 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)
- +3Description length 953: 120–800 characters recommended
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -256 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +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: 78.