BD smyx-fish-fry-growth-measurement-analysis
Through fixed cameras of fry tanks (a known-size reference object such as a scale ruler, standard coin or calibration board must be placed in the view), the system periodically (e.g. daily or weekly) captures fry images and uses AI vision analysis to measure body length (from snout to tail-fin tip, in mm), record individual growth rate (mm/day) and draw the growth curve. | 通过鱼苗缸固定摄像头（需放置已知尺寸的参照物，如刻度尺、标准硬币或标定板），定期（如每天或每周）拍摄鱼苗图像，利用 AI 视觉分析技术测量鱼苗体长（从吻端到尾鳍末端，单位 mm），记录个体的生长速率（mm/天），并绘制生长曲线。系统自动采集图像，生成生长报告，异常时提示（如生长停滞）。
Through fixed cameras of fry tanks (a known-size reference object such as a scale ruler, standard coin or calibration board must be placed in the view), the…
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 2213 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
- -271 emoji in the instructions: noise for the model
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 519: 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.