AI Model Wechat

What it does

When your agent uses it

• Developing WeChat Mini Programs (小程序
• Wx.cloud-based apps) that need AI capabilities

Example prompts

• “/ai-model-wechat”

Requirements

• Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Check base library version - Ensure 3.7.1+ for AI support
2. 2Use callbacks for UI updates - onText is great for real-time display
3. 3Check for [DONE] - When using eventStream, check event.data === "[DONE]" to stop
4. 4Handle errors gracefully - Wrap AI calls in try/catch
5. 5Remember the data wrapper - streamText params must be wrapped in data: {...}

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript and typescript).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AI Model Wechat loads about 1.4k tokens when it runs. Until then it costs about 153 tokens; SKILL.md has 261 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~153

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 261 words, ~1,449 tokens.

name

ai-model-wechat

description

Use this skill when developing WeChat Mini Programs (小程序, 企业微信小程序, wx.cloud-based apps) that need AI capabilities. Features text generation (generateText) and streaming (streamText) with callback support (onText, onEvent, onFinish) via wx.cloud.extend.AI. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended) and DeepSeek (deepseek-v3.2 recommended). API differs from JS/Node SDK - streamText requires data wrapper, generateText returns raw response. NOT for browser/Web apps (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (not supported).

alwaysApply

false

// app.js
App({
  onLaunch: function() {
    wx.cloud.init({ env: "<YOUR_ENV_ID>" });
  }
})

const model = wx.cloud.extend.AI.createModel("hunyuan-exp");

const res = await model.generateText({
  model: "hunyuan-2.0-instruct-20251111",  // Recommended model
  messages: [{ role: "user", content: "你好" }],
});

// ⚠️ Return value is RAW model response, NOT wrapped like JS/Node SDK
console.log(res.choices[0].message.content);  // Access via choices array
console.log(res.usage);                        // Token usage

const model = wx.cloud.extend.AI.createModel("hunyuan-exp");

// ⚠️ Parameters MUST be wrapped in `data` object
const res = await model.streamText({
  data: {                              // ⚠️ Required wrapper
    model: "hunyuan-2.0-instruct-20251111",  // Recommended model
    messages: [{ role: "user", content: "hi" }]
  },
  onText: (text) => {                  // Optional: incremental text callback
    console.log("New text:", text);
  },
  onEvent: ({ data }) => {             // Optional: raw event callback
    console.log("Event:", data);
  },
  onFinish: (fullText) => {            // Optional: completion callback
    console.log("Done:", fullText);
  }
});

// Async iteration also available
for await (let str of res.textStream) {
  console.log(str);
}

// Check for completion with eventStream
for await (let event of res.eventStream) {
  console.log(event);
  if (event.data === "[DONE]") {       // ⚠️ Check for [DONE] to stop
    break;
  }
}

interface WxStreamTextInput {
  data: {                              // ⚠️ Required wrapper object
    model: string;
    messages: Array<{
      role: "user" | "system" | "assistant";
      content: string;
    }>;
  };
  onText?: (text: string) => void;     // Incremental text callback
  onEvent?: (prop: { data: string }) => void;  // Raw event callback
  onFinish?: (text: string) => void;   // Completion callback
}

interface WxStreamTextResult {
  textStream: AsyncIterable<string>;   // Incremental text stream
  eventStream: AsyncIterable<{         // Raw event stream
    event?: unknown;
    id?: unknown;
    data: string;                      // "[DONE]" when complete
  }>;
}

// Raw model response (OpenAI-compatible format)
interface WxGenerateTextResponse {
  id: string;
  object: "chat.completion";
  created: number;
  model: string;
  choices: Array<{
    index: number;
    message: {
      role: "assistant";
      content: string;
    };
    finish_reason: string;
  }>;
  usage: {
    prompt_tokens: number;
    completion_tokens: number;
    total_tokens: number;
  };
}

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/cloudbase/references/ai-model-wechat of LeoYeAI/openclaw-master-skills.

Open the folder on GitHubat commit e5199b5

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in LeoYeAI/openclaw-master-skills, which our catalogue first saw on October 9, 2026.

• infometa/workbuddyskillsskills/cloudbase/references/ai-model-wechatplugins/codebuddy-plugins-official/plugins/cloudbase/skills/cloudbase/references/ai-model-wechat