CD ref-site-ui-tokens
用户说「参考 X 网站改 UI / 照着 X 的风格做 / X 那种配色」时的落地流程。在没有浏览器的机器上（agent-browser、playwright 都没装，或 Chrome/Edge 不在标准路径）用 curl + 标准库 Python 抓下目标站的真实设计 token（颜色、圆角、字重、字号、间距），再据此改本地样式表。含一个可直接跑的抓取脚本 scripts/fetch_tokens.py，以及「借什么 / 不借什么」的取舍框架与常见坑。
用户说「参考 X 网站改 UI / 照着 X 的风格做 / X 那种配色」时的落地流程。在没有浏览器的机器上（agent-browser、playwright 都没装，或 Chrome/Edge 不在标准路径）用 curl + 标准库 Python 抓下目标站的真实设计…
As a process D 46/100 · Unfinished process — 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: 3. 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 "agent_created" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "visibility"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 749 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 229: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.