BF webflow-china-speed
Webflow + Cloudflare Worker 中国大陆访问加速专项技能。当用户想要优化 Webflow 网站在中国大陆的访问速度时,必须使用此技能。 触发场景:用户提到 Webflow 网站速度慢、中国大陆无法访问、CF Worker 反向代理优化、Google 资源被屏蔽、Webflow CDN 加速、 字体加载慢、视频加载慢、jsdmirror 替换、R2 缓存、ICP 备案合规、EdgeOne 国内节点、双域名双 CDN 架构、DNS 地理分流、 多项目扩展、Geo-DNS、华为云 DNS、腾讯 EdgeOne、大陆备案最小成本方案等话题。 即使用户只是问"我的 Webflow 网站在中国大陆很慢怎么办"也要触发。
Webflow + Cloudflare Worker 中国大陆访问加速专项技能。当用户想要优化 Webflow 网站在中国大陆的访问速度时,必须使用此技能。 触发场景:用户提到 Webflow 网站速度慢、中国大陆无法访问、CF Worker 反向代理优化、Google 资源被屏蔽、Webflow CDN 加速、…
As a process F 33/100 · Will not run — References files that are not bundled: assets/{host}/{path}_{base64(queryString)}
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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") - warning
missing-refreference to a missing file: assets/{host}/{path}_{base64(queryString)}
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: assets/{host}/{path}_{base64(queryString)}
- 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
- 30Running it twice. 1 mutating operations with no state check
- 100Steps. 51 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3342 tokens
- low The response is described with custom markup (10 tags): a typed call is more reliable
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
- -218 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 319: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 51 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.