BD smyx-separation-anxiety-relief-analysis
AI-powered pet separation anxiety detection & relief when the owner leaves home. Real-time monitoring via smart camera detects typical anxiety signs—continuous vocalization, pacing, scratching doors/windows, destructive chewing. When anxiety reaches preset thresholds, the system auto-triggers comfort actions (play owner's pre-recorded voice, dispense treats via smart feeder, activate interactive toys) to reduce anxiety and destructive behavior, improving pet welfare. Scenarios: pet households (especially office workers / frequent travelers), pet boarding centers. | 通过智能家居摄像头（宠物摄像头）实时监测主人离家后宠物的行为，检测持续性发声（哀嚎、嚎叫）、来回踱步、抓挠门窗或破坏家具等分离焦虑典型表现。当焦虑行为达到预设阈值时，自动触发安抚动作，包括播放主人预录的安抚语音、联动智能零食机投掷零食、或启动互动玩具（如自动逗猫棒），减轻宠物独处时的焦虑，减少破坏行为，提升宠物福利。应用场景：宠物家庭（尤其上班族、经常出差的主人）、宠物寄养中心。
AI-powered pet separation anxiety detection & relief when the owner leaves home.
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 1735 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
- -284 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 763: 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.