BD design
|-。自动学习用户视觉偏好,适配UI/图形/视频/印刷多媒介,持续进化设计风格记忆。自适应设计偏好引擎。通过观察用户在设计过程中的选择、反馈与反应,自动提取并沉淀视觉偏好模式。Use when 需要设计创作、UI设计、海报制作、品牌视觉时使用。不适用于3D建模和动画制作。适用于独立开发者、企业团队和自动化工作流场景。
|-。自动学习用户视觉偏好,适配UI/图形/视频/印刷多媒介,持续进化设计风格记忆。自适应设计偏好引擎。通过观察用户在设计过程中的选择、反馈与反应,自动提取并沉淀视觉偏好模式。Use when 需要设计创作、UI设计、海报制作、品牌视觉时使用。不适用于3D建模和动画制作。适用于独立开发者、企业团队和自动化工作流场景。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Block scalar header includes extra characters: |-。自动学习用户视觉偏好,适配UI/图形/视频/印刷多媒介,持续进化设计风格记忆。自适应设计偏好引擎。通过观察用户在设计过程中的选择、反馈与反应,自动提取并沉淀视觉偏好模式。Use at line 11, column 16: description: |-。自动学习用户视觉偏好,适配UI/图形/视频/印刷多媒介,持续进化设计风格记忆。自适应设计偏好引擎。通过观察用户在设计过程中的选… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 159 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "summary_zh" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (design) differs from the folder (design-toolkit)
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 42 steps
- 100Execution cost. Instruction body is 1981 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 18 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 159: enough signal without eating the budget
- +4Structure: 45 headings
- +3Step-by-step instructions: 42 items
- +4Has examples (11 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.