BD smyx-snake-stomatitis-detection-analysis
Through fixed enclosure cameras, the system captures high-definition images of the moment a snake opens its mouth (yawning, post-feeding, or oral examination) and uses AI visual analysis to detect oral mucosa color (normal pink, mild inflammation red, severe inflammation dark-red or pale), the presence of pus points (white or yellow dots), ulcers, or necrotic tissue (irregular depressions, necrotic patches), comprehensively. | 通过蛇箱固定摄像头，捕捉蛇张口（打哈欠、进食后或口腔检查）时的瞬间高清图像，利用 AI 视觉分析技术检测口腔黏膜颜色（正常粉红色、轻度炎症红色、重度炎症暗红或苍白）、有无脓点（白色或黄色点状物）、溃疡或腐肉（不规则凹陷、坏死组织），综合输出口炎风险等级（低/中/高）。该技能有助于早期发现蛇类口腔感染，预防败血症。
Through fixed enclosure cameras, the system captures high-definition images of the moment a snake opens its mouth (yawning, post-feeding, or oral examination)…
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 2498 tokens
- 100Running it twice. No mutating operations
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
- -281 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 588: 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: 69.