Wechat Video Channel Publish logo

Wechat Video Channel Publish

Community
appleweiping
wechat-video-channel-publish

Use when the user wants to log into 微信视频号, validate cookie state, upload videos, set scheduled publish time, fill long description, set a cover image, or save drafts through a local Playwright CLI.

Overview

Publisherappleweiping
RepositoryAGENT_RESOURCE
Skill namewechat-video-channel-publish
Stars
78
Forks
10
Bundled files
18
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 18 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by appleweiping on GitHub. Read the source before you install it.

Installation

Install the Wechat Video Channel Publish AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/appleweiping/AGENT_RESOURCE/tree/master/skills/vipin/wechat-video-channel-publish
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/appleweiping/AGENT_RESOURCE.git /tmp/AGENT_RESOURCE
mkdir -p .claude/skills
cp -r /tmp/AGENT_RESOURCE/skills/vipin/wechat-video-channel-publish .claude/skills/wechat-video-channel-publish
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wechat Video Channel Publish in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wechat Video Channel Publish on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wechat Video Channel Publish is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WeChat Video Channel Publish

This skill packages a focused 微信视频号 publishing workflow for local agent execution.

Use it when the task is specifically about:

  • 视频号扫码登录
  • 上传短视频
  • 设置标题、标签、正文长描述
  • 设置封面图
  • 定时发布
  • 保存草稿(best effort;平台 UI 可能在部分状态下拒绝)
  • 发布后补评论

Quick Start

  1. Read references/runtime-requirements.md.
  2. Build the CLI if dist/cli.js does not exist.
  3. Run tencent login or tencent check.
  4. Run tencent upload with absolute video and cover paths.
  5. If the task uses a publishing queue, first normalize it into direct CLI arguments.
  6. Before any public repo push, read references/privacy-checklist.md.

Workflow

Step 1: Prepare Runtime

  • Run all commands in the repo root.
  • If needed, execute:
    • npm install
    • npx playwright install chromium
    • npm run build

Step 2: Login or Reuse Cookie

  • For first-time login:
    • node dist/cli.js tencent login --account <name>
  • For validation:
    • node dist/cli.js tencent check --account <name>

The cookie file is stored outside the repo by default and must never be committed.

Step 3: Publish a Video

  • Read references/publish-workflow.md.
  • Use absolute paths for --file and --cover.
  • Supported fields:
    • --title
    • --tags
    • --caption
    • --cover
    • --pinned-comment
    • --schedule
    • --category
    • --draft

Step 4: Validate Carefully

  • Prefer --draft when verifying a new selector path or runtime change, but do not combine it with --schedule.
  • Treat cover and pinned-comment as runtime-sensitive features.
  • If UI changes break these steps, keep login and upload logic intact and narrow the failure to the affected selector flow.

Step 5: Repo Hygiene

  • Keep cookies, screenshots, local logs, and temporary exports out of git.
  • When sharing publicly, include only reusable code, templates, and references.

Resource Loading Rules

  • Read references/runtime-requirements.md before execution.
  • Read references/publish-workflow.md when mapping a publishing plan into CLI arguments.
  • Read references/privacy-checklist.md before creating or updating a public repository.

Output Expectations

  • The agent should execute the real CLI when feasible.
  • The agent should report what fields were actually attempted at runtime.
  • If a selector-dependent step is flaky, the agent should say exactly which sub-step failed:
    • login
    • upload
    • caption
    • cover
    • comment

Guardrails

  • Do not print or commit cookie JSON.
  • Do not embed user-specific absolute paths in committed docs except as obvious placeholders.
  • Do not claim comment pinning is fully reliable unless it was verified in the current session.
  • Do not claim --draft + --schedule is supported; use --schedule without --draft for real scheduled publishing.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Wechat Video Channel Publish AI skill do?

Use when the user wants to log into 微信视频号, validate cookie state, upload videos, set scheduled publish time, fill long description, set a cover image, or save drafts through a local Playwright CLI.

Why use Wechat Video Channel Publish on TypingMind?

Because you install it once and use it with any model. Wechat Video Channel Publish is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wechat Video Channel Publish in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/appleweiping/AGENT_RESOURCE/tree/master/skills/vipin/wechat-video-channel-publish. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wechat Video Channel Publish?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wechat Video Channel Publish?

As many as you like. As long as a model supports skills, you can use Wechat Video Channel Publish with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wechat Video Channel Publish AI skill free?

Yes. It is published on GitHub by appleweiping under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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