AD smyx-pet-grooming-stress-behavior-analysis
Triggers when a user provides a pet grooming session video URL or file for analysis; supports local video uploads or network URLs to call server-side APIs for stress behavior recognition, detecting struggling, panting, tail tucking and other stress signals during grooming, outputting stress level grading to help groomers intervene promptly. Application scenarios: pet grooming shop cameras, veterinary clinics, pet care services. | 当用户提供宠物美容过程视频URL或文件时，触发本技能进行应激行为分析；支持通过上传本地视频或网络视频URL，调用服务端API进行识别，检测挣扎、张口喘气、尾巴夹紧等应激行为信号，输出应激等级，帮助美容师及时干预，减少宠物应激伤害，提升服务体验。应用场景：宠物美容店摄像头、宠物医院、宠物护理服务。
Triggers when a user provides a pet grooming session video URL or file for analysis; supports local video uploads or network URLs to call server-side APIs for…
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 1686 tokens
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
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
- -264 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 582: enough signal without eating the budget
- +4Structure: 22 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.