BF smyx-frog-skin-moisture-assessment-analysis
Through fixed cameras in rainforest tanks or vivariums, the system captures high-definition images of the dorsal or lateral skin of frogs (such as tree frogs, horned frogs, dart frogs), and uses AI visual analysis to detect skin glossiness (specular reflection intensity) and assess skin moisture levels. | 通过雨林缸或饲养箱固定摄像头，拍摄蛙类（如树蛙、角蛙、箭毒蛙）的背部或侧身皮肤高清图像，利用 AI 视觉分析技术检测皮肤的光泽度（反光强度），评估皮肤的湿润程度。健康的蛙类皮肤应湿润、有光泽；当皮肤干燥时，光泽度显著下降，甚至出现皱褶或白膜。
Through fixed cameras in rainforest tanks or vivariums, the system captures high-definition images of the dorsal or lateral skin of frogs (such as tree frogs…
As a process F 32/100 · Will not run — 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: 16. 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 32/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2597 tokens
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 428: 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.