BD smyx-social-interaction-analysis-analysis
AI-powered pet social interaction analysis for multi-pet households. Uses pose recognition and behavior classification to detect cat-cat, dog-dog, and cat-dog interactions—sniffing, chasing, biting, fleeing, hiding, playing—then records duration, frequency, initiator and receiver to generate a social-behavior report. Helps owners understand pet relationships, spot aggression or stress sources, and promote harmonious cohabitation. Scenarios: multi-pet homes, pet boarding centers, pet daycare, animal behavior clinics. | 通过多宠家庭固定摄像头，分析宠物之间（猫-猫、狗-狗、猫-狗等）的互动视频，利用姿态识别和行为分类模型检测嗅闻、追逐、撕咬、逃跑、躲避、玩耍等行为类型，记录每种行为的持续时间、频次以及发起者，生成社交行为报告。帮助主人了解宠物间的社交关系，识别潜在的攻击行为或压力源，促进多宠和谐共处。应用场景：多宠家庭（多猫/多狗/猫狗混养）、宠物寄养中心、宠物日托班、宠物行为诊所。
As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
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 1679 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
- -268 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 709: enough signal without eating the budget
- +4Structure: 25 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.