BB china-auth-integration
Implement Chinese authentication systems including WeChat Login, Alipay Login, phone SMS verification, and real-name verification (实名认证). Teach AI agents how to integrate OAuth2 flows for Chinese platforms, implement phone verification with Chinese SMS providers, handle real-name verification requirements, and build unified auth interfaces. Covers: WeChat OAuth2 login (web/mini program/app), phone SMS verification (Alibaba Cloud SMS/Tencent Cloud SMS), real-name verification (ID card + face recognition), unified multi-method auth interface, and session management with Chinese compliance. Triggers on: 微信登录, wechat login, 支付宝登录, alipay login, 手机验证码, SMS verification china, 实名认证, real-name verification, 中国身份验证, china authentication, 微信OAuth, wechat oauth2, 短信验证码, SMS code verification, 统一登录, unified login, 中国用户认证, china user auth
Implement Chinese authentication systems including WeChat Login, Alipay Login, phone SMS verification, and real-name verification (实名认证).
As a process B 66/100 · Nearly there — weak spots: result and completion, failures and branches, running it twice
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: 2. 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")
Process rating: all ten parameters 66/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 1 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2026 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +3Description length 838: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -231 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 18 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.