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Wjs Voicedrop Post Processing

Community
jianshuo
wjs-voicedrop-post-processing

Use when a newly mined VoiceDrop article needs automated post-processing — invoked headless by the 5-minute poller (launchd com.jianshuo.voicedrop-postprocess) with the article stem as argument. Triggers — "/wjs-voicedrop-post-processing <stem>".

Overview

Publisherjianshuo
Repositoryclaude-skills
Skill namewjs-voicedrop-post-processing
Stars
137
Forks
22
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Wjs Voicedrop Post Processing 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/jianshuo/claude-skills/tree/main/wjs-voicedrop-post-processing
  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/jianshuo/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/wjs-voicedrop-post-processing .claude/skills/wjs-voicedrop-post-processing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wjs Voicedrop Post Processing 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 Wjs Voicedrop Post Processing 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 Wjs Voicedrop Post Processing 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.

VoiceDrop 文章后处理

输入:文章 stem,由调用参数给出($ARGUMENTS)。

运行环境:无人值守 claude -p,voicedrop MCP 已接好(读文章/写版本工具可用;发布、删除、社区、花钱类工具已被调用方禁用)。不要问任何问题,跑完即退。

流程

  1. 用 voicedrop MCP 的读文章工具取回该 stem 的文章全文与元数据。读不到就重试一次,再失败以非零退出(轮询器下一轮会重试)。
  2. 【后处理动作——待建硕定义,目前是骨架版:只检查,不改动文章】
    • 检查正文非空、标题存在
    • 最后输出一行:postprocess ok: <stem> — <标题>(<字数>字)

铁律(同夜班编辑)

  • 绝不发布、绝不删除、绝不碰文风库和社区。
  • 将来若要改文章,只能走「写新版本」,不切 head。

待定义

后处理具体做什么(配图 / 打标签 / 质量评分 / 生成摘要…)想好后,替换第 2 步即可,轮询器不用动。

Frequently asked questions

What does the Wjs Voicedrop Post Processing AI skill do?

Use when a newly mined VoiceDrop article needs automated post-processing — invoked headless by the 5-minute poller (launchd com.jianshuo.voicedrop-postprocess) with the article stem as argument. Triggers — "/wjs-voicedrop-post-processing <stem>".

Why use Wjs Voicedrop Post Processing on TypingMind?

Because you install it once and use it with any model. Wjs Voicedrop Post Processing 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 Wjs Voicedrop Post Processing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jianshuo/claude-skills/tree/main/wjs-voicedrop-post-processing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wjs Voicedrop Post Processing?

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 Wjs Voicedrop Post Processing?

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

Is the Wjs Voicedrop Post Processing AI skill free?

Yes. It is published on GitHub by jianshuo under the MIT 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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