BF smyx-leaf-aging-fall-prediction-analysis
Using a fixed indoor camera to continuously capture leaf images of houseplants from the same angle every day, AI vision techniques detect leaf color changes (green → yellow → brown), loss of glossiness (reduced surface reflectance), and formation of the abscission zone at the petiole base (angle change). | 通过室内绿植固定摄像头连续采集叶片图像（每天同一角度），利用AI视觉分析技术检测叶片颜色变化（从绿到黄再到褐）、光泽度下降（叶面反光减弱）、叶柄基部离层形成（角度变化）等老化进程，并基于历史图像序列的时间序列模型预测未来3-7天内叶片脱落的风险时段。系统每日生成老化报告，当预测即将落叶时推送提醒（如'富贵竹下位叶预计3天后脱落，可提前剪除以保持美观'）。
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: 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 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 1599 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
- -254 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 486: 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.