AF wechatpay-payment-integration
微信支付（WeChat Pay）相关问题的统一入口，处理与微信支付接入、产品、开发、运营、品牌经营相关的咨询，提供产品选型、官方示例代码、接入质量评估、答疑与排障。Use when user mentions "微信支付", "微信收款", "WeChat Pay", "JSAPI", "APP支付", "H5支付", "Native支付", "扫码支付", "付款码", "小程序支付", "合单支付", "医保支付", "微信支付分", "分账", "转账", "委托代扣", "周期扣款", "代金券", "商家券", "特约商户进件", "服务商", "sub_mchid", "APIv2", "APIv3", "回调", "签名", "证书", "错误码", "OpenID", "品牌经营", "品牌经营平台", "品牌门店", "商家名片", "名片会员", "商品券", "摇一摇有优惠", "摇优惠", "品牌入驻", or asks to "推荐支付方式/产品选型", "要接口或示例代码", "做接入代码质量审查/上线前检查", "解释字段含义或接口规则", "排查报错/查单/支付问题".
微信支付（WeChat Pay）相关问题的统一入口，处理与微信支付接入、产品、开发、运营、品牌经营相关的咨询，提供产品选型、官方示例代码、接入质量评估、答疑与排障。Use when user mentions "微信支付", "微信收款", "WeChat Pay", "JSAPI", "APP支付"…
As a process F 35/100 · Will not run — References files that are not bundled: references/基础概念及业务介绍.md, assets/wechatpay-docs-guide.md, references/接入质量检查清单.md
How to improve
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/基础概念及业务介绍.md - warning
missing-refreference to a missing file: assets/wechatpay-docs-guide.md - warning
missing-refreference to a missing file: references/接入质量检查清单.md - warning
missing-refreference to a missing file: references/文档检索与问答.md - warning
missing-refreference to a missing file: references/APIv3接口动态排障.md
Process rating: all ten parameters 35/100
- 0Tools and files. 5 referenced file(s) missing: references/基础概念及业务介绍.md, assets/wechatpay-docs-guide.md, references/接入质量检查清单.md
- 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
- 100Steps. 33 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 922 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 12 example trigger phrases
- +3Description length 508: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.