Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wangjianqi/AppStore --skill 22-chinese-llm-ecosystemgit clone --depth 1 https://github.com/wangjianqi/AppStoreWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wangjianqi/appstore/22-chinese-llm-ecosystem)<a href="https://agentmods.dev/skills/wangjianqi/appstore/22-chinese-llm-ecosystem"><img src="https://agentmods.dev/badge/skills/wangjianqi/appstore/22-chinese-llm-ecosystem/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wangjianqi/appstore/22-chinese-llm-ecosystem"><img src="https://agentmods.dev/badge/skills/wangjianqi/appstore/22-chinese-llm-ecosystem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00878 |
| Opus 5 | $0.00026 | $0.00439 |
| Sonnet 5 | $0.00011 | $0.00176 |
| Haiku 4.5 | $0.00005 | $0.00088 |
Grade A, and why
chinese-llm-ecosystem scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
80% identical to smart-search — 199 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
国内大模型生态
API 接入
OpenAI 兼容格式
大多数国产大模型支持 OpenAI 兼容 API 格式,只需修改 baseURL 和 model 参数:
| 提供商 | baseURL | 模型名 |
|---|---|---|
| 通义千问 | https://dashscope.aliyuncs.com/compatible-mode/v1 | qwen-plus / qwen-turbo / qwen-max |
| DeepSeek | https://api.deepseek.com/v1 | deepseek-chat / deepseek-reasoner |
| 智谱 GLM | https://open.bigmodel.cn/api/paas/v4 | glm-4 / glm-4-flash |
| 月之暗面 | https://api.moonshot.cn/v1 | moonshot-v1-8k / moonshot-v1-32k |
| 讯飞星火 | https://spark-api-open.xf-yun.com/v1 | generalv3.5 / 4.0Ultra |
Swift 调用示例
struct QwenService: LLMServiceProtocol {
private let baseURL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
private let apiKey: String
func chat(messages: [ChatMessage]) async throws -> ChatResponse {
var request = URLRequest(url: URL(string: "\(baseURL)/chat/completions")!)
request.httpMethod = "POST"
request.setValue("Bearer \(apiKey)", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
let body: [String: Any] = [
"model": "qwen-plus",
"messages": messages.map { ["role": $0.role.rawValue, "content": $0.content] }
]
request.httpBody = try JSONSerialization.data(withJSONObject: body)
let (data, _) = try await URLSession.shared.data(for: request)
return try JSONDecoder().decode(ChatResponse.self, from: data)
}
}
国内 AI 合规
算法备案判断
- App 内提供 AI 对话功能 → 通常需要备案
- 仅调用 API 展示结果 → 模型提供方已备案,App 方视情况
- 本地模型推理 → 通常不需要
- 仅内部使用 AI 辅助开发 → 不需要
AI 生成内容标识
- 显式标识:在 AI 生成内容旁显示"AI 生成"标签
- 隐式标识:在 AI 生成图片中嵌入数字水印
- 元数据标识:在内容元数据中标注 AI 生成
隐私政策 AI 条款
- 说明 AI 功能的数据处理方式
- 说明对话内容是否存储及存储位置
- 提供关闭 AI 功能的选项
- 声明 AI 生成内容仅供参考
数据出境合规
风险评估
- 调用海外 API(OpenAI/Claude)→ 用户数据出境 → 需评估
- 调用国内 API → 数据不出境 → 合规
- 后端代理 + 脱敏 → 部分合规
推荐方案
面向国内用户的 App,优先使用国内大模型 API,避免数据出境合规风险。
合规检查清单
- AI 功能已在隐私政策中说明
- AI 生成内容已添加标识
- 用户可选择关闭 AI 功能
- 已评估是否需要算法备案
- 已评估数据出境合规性
- AI 生成内容已过滤违法信息
- 已添加 AI 生成内容免责声明
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 86 lines · 53 tokens per session scan A 66dd36b84fdc
chinese-llm-ecosystem is a skill published in the GitHub repository wangjianqi/AppStore (11 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 878 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to smart-search, differing in 199 lines, and is treated as a copy.
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