AD smyx-pet-hospital-waiting-anxiety-analysis
Triggers when a user provides a pet hospital waiting area video URL or file for analysis; supports local video uploads or network URLs to call server-side APIs for anxiety-related behavior recognition, detecting open-mouth panting intensity, limb/torso trembling amplitude, ear-flattening degree and other stress signals, outputting a standardized anxiety level (1-5) to help medical staff identify high-stress pets and prioritize care or comfort (without diagnosing diseases or prescribing treatment). Application scenarios: pet hospital waiting areas, veterinary clinics, pet care institutions. Development reason: optimize visit workflow and reduce stress-related harm. | 当用户提供候诊区宠物视频的URL或文件时，触发本技能进行焦虑行为信号分析；支持通过上传本地视频或网络视频URL，调用服务端API检测张口喘气强度、四肢/躯干颤抖幅度、耳朵后贴程度等应激信号，综合输出标准化焦虑等级（1-5级），帮助医护人员识别高应激宠物并优先安排就诊或安抚（不诊断疾病、不提供治疗方案）。应用场景：宠物医院候诊区、动物诊所、宠物护理机构。
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 1441 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 852: 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.