BC chem-viz
化学可视化引擎。将抽象化学过程转化为交互式可视化HTML页面， 让学生"看见"化学：分子转得起来、电子流看得见、平衡拉得动、流程拆得开。 支持9类可视化：分子结构3D/氧化还原/化学平衡/电化学/工艺流程/有机3D/晶胞/实验装置/离子平衡。 核心技术：纯Canvas2D+手动3D数学（零外部依赖，file://协议100%可靠）， 附带3Dmol.js/JSXGraph/Three.js备选方案与常见陷阱修复指南。 与chem-coach联动，两级验证流程保证产物质量。
化学可视化引擎。将抽象化学过程转化为交互式可视化HTML页面， 让学生"看见"化学：分子转得起来、电子流看得见、平衡拉得动、流程拆得开。 支持9类可视化：分子结构3D/氧化还原/化学平衡/电化学/工艺流程/有机3D/晶胞/实验装置/离子平衡。…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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: 4. 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") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en" - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "trigger_keywords"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 68 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1628 tokens
- 100Running it twice. No mutating operations
- low 13 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 238: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 68 items
- +4Has examples (8 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.