AD smyx-excitement-calming-guide-analysis
AI-powered pet over-excitement detection & calming guidance. Real-time camera analysis tracks movement speed, jump height, spin laps, and jumping-on-people actions to score excitement level. When the score exceeds safety thresholds, the system auto-issues calming cues (play owner's voice command like 'sit'/'slow down', soft prompt tone, release calming pheromone, dim lights). Helps prevent injuries from over-excitement and keeps the household safe. Scenarios: lively pet households, pet boarding centers, pet daycare, dog training schools. | 通过宠物活动区的固定摄像头实时分析宠物的运动状态，检测狂跳、高速转圈、反复扑人等极度兴奋行为，评估兴奋等级。当兴奋等级超过安全阈值时，自动输出冷静引导指令，包括播放主人的语音口令（如"坐下"、"慢下来"）、发出柔和提示音，或联动环境设备（如释放宠物镇静信息素、调暗灯光），预防宠物因过度兴奋而撞伤、摔倒或伤人，维护家庭安全。应用场景：宠物家庭（尤其活泼好动的犬猫）、宠物寄养中心、宠物日托班、宠物训练学校。
As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
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 35/100
- 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
- 20When it triggers. No condition that starts the skill
- 25Steps. 1 steps
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1697 tokens
- 100Running it twice. No mutating operations
- low 13 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
- -280 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 749: enough signal without eating the budget
- +4Structure: 23 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.