AD wechatpay-global-payment
微信支付境外（跨境）平台接入解决方案，7 大支付产品覆盖境外 6 大典型支付场景，同时提供跨境分账、子商户进件、海关报关等扩展能力。支持产品选型/示例代码指引/业务速查/质量评估/排障五大能力，支持中文、English、日本語、한국어、Français、Español、Português、Русский、العربية 九语言自适应。Use when user mentions '微信支付', '境外微信支付', '海外微信支付', '跨境支付', '跨境电商支付', '境外商户接入', '海外收款', 'apihk', '跨境分账', '境外子商户进件', '海关报关', '境外回调', or asks in English ('overseas WeChat Pay', 'cross-border payment', 'Quick Pay integration'), Japanese ('海外決済', 'WeChat Pay接入'), Korean ('해외 결제', '위챗페이 연동'), French ('paiement transfrontalier', 'intégration WeChat Pay'), Spanish ('pago transfronterizo', 'integración WeChat Pay'), Portuguese ('pagamento transfronteiriço', 'integração WeChat Pay'), Russian ('трансграничный платёж', 'интеграция WeChat Pay'), or Arabic ('الدفع عبر الحدود', 'تكامل WeChat Pay').
微信支付境外（跨境）平台接入解决方案，7 大支付产品覆盖境外 6…
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
- 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: 16. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en"
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 (wechatpay-global-payment) differs from the folder (wechatpay-global-payment1)
- 100Tools and files. No external tools needed
- 100Steps. 19 steps
- 100Execution cost. Instruction body is 846 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
- +4No input/output examples
- -226 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 758: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 19 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.