BD smyx-pet-treadmill-intensity-analysis
AI-powered pet treadmill exercise intensity analysis combined with optional heart-rate band data. Detects stride frequency, limb extension, and respiratory rate from treadmill video to assess current exercise load (Low/Medium/High) and provide real-time pacing suggestions. Scenarios: smart pet treadmills (dog/cat), pet weight-loss training centers, pet rehabilitation. | 通过宠物跑步机内置或外置摄像头实时分析宠物跑步视频，检测步频、四肢伸展幅度、呼吸频率等运动姿态指标，并结合可选的心率带数据（蓝牙心率监测），综合评估当前运动强度等级（低/中/高），辅助宠物主人科学控制运动量，防止过度疲劳或运动损伤。应用场景：宠物跑步机（犬用/猫用）、宠物减肥训练中心、宠物康复理疗。
As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
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 1470 tokens
- 100Running it twice. No mutating operations
- low 11 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
- -265 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 523: enough signal without eating the budget
- +4Structure: 21 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: 69.