AD smyx-picky-eater-detection-analysis
Triggers when a user provides a video of a pet feeding bowl area for analysis; supports local video uploads or network URLs to call server-side APIs for picky-eater behavior detection, identifying behaviors such as pushing kibble out of the bowl, picking only treats/freeze-dried bites, or sniffing then leaving without eating; records frequency and outputs feeding-adjustment suggestions to prevent malnutrition. Application scenarios: smart pet feeders, pet boarding centers, pet hospital inpatient wards. | 当用户提供宠物食盆区域视频时，触发本技能进行选择性拒食行为识别；支持通过上传本地视频或网络视频URL，调用服务端API识别宠物把主粮拨出食盆、只挑拣零食/冻干、嗅闻后离开等挑食行为，记录发生频率，连续异常时输出喂养调整建议，预防营养不均衡（不诊断疾病）。应用场景：智能喂食器、宠物寄养中心、宠物医院住院部。
As a process D 38/100 · 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 38/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 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 1328 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
- -254 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 663: 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.