BC china-notification-service
Implement multi-channel notification services for Chinese applications using WeChat Template Messages, WeChat Subscription Messages, SMS (Alibaba Cloud/Tencent Cloud), DingTalk Bot, Feishu Bot, and Email. Teach AI agents how to build unified notification dispatch systems, handle rate limits, implement priority-based routing, and ensure delivery compliance. Covers: unified notification dispatch interface, WeChat template/subscription messages, SMS via Chinese cloud providers, enterprise IM bot notifications (DingTalk/Feishu), and notification compliance and rate limiting. Triggers on: 中国通知服务, china notification service, 微信模板消息, wechat template message, 微信订阅消息, wechat subscription message, 短信通知, SMS notification china, 钉钉机器人通知, dingtalk bot notification, 飞书机器人通知, feishu bot notification, 多渠道通知, multi-channel notification, 通知分发, notification dispatch, 消息推送, message push china, 通知合规, notification compliance
Implement multi-channel notification services for Chinese applications using WeChat Template Messages, WeChat Subscription Messages, SMS (Alibaba…
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, 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 · 2
✓ No critical or high findings
Medium and low: 2
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low Exfiltration
exfil-secret-in-urlSKILL.md:99Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)`https://api.weixin.qq.com/cgi-bin/message/template/send?access_token=…
placeholder -
low Exfiltration
exfil-secret-in-urlSKILL.md:135Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)`https://api.weixin.qq.com/cgi-bin/message/subscribe/send?access_token=…
placeholder
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 62/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 20 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2471 tokens
- 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 916: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -223 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 22 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.