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Mass Line

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HughYau
mass-line

群众路线:从持有真实情况的多方(用户、使用者、代码库、日志、运行结果)收集分散意见,系统化为方案,再带回去对齐与检验,循环改进。当多方意见分歧、需要汇总零散反馈、方案要拿回给真实使用者确认、或你发觉自己在闭门造车时触发;信息源单一且完整、处于执行阶段时不触发。 English: Mass line. Collect scattered input from everyone who holds ground truth (users, operators, codebase, logs, runtime results), synthesize it into a coherent plan, take it back for alignment and validation, and iterate. Trigger when inputs conflict, feedback must be consolidated, a plan needs sign-off from real users, or you sense you are designing in isolation; skip when there is a single complete source and the work is pure execution.

Overview

PublisherHughYau
Repositoryqiushi-skill
Skill namemass-line
Stars
3.8K
Forks
285
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Mass Line 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.
  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/HughYau/qiushi-skill.git /tmp/qiushi-skill
mkdir -p .claude/skills
cp -r /tmp/qiushi-skill/skills/mass-line .claude/skills/mass-line
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mass Line 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 Mass Line 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 Mass Line 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.

群众路线

"从群众中来,到群众中去。" —— 《关于领导方法的若干问题》

investigation-first 的分工:调查研究是"我去弄清事实";群众路线是"把整理后的方案带回给持有真实情况的人和系统检验",重点在多方分歧的处理返回验证

AI 语境下的"群众"

原义映射
群众的实际经验代码库既有模式、注释、惯例
基层第一手信息git history、测试用例、错误日志
群众对方案的反馈运行结果、测试失败、用户的真实使用反馈
多方意见综合文档 + 代码 + 运行结果 + 用户描述的交叉验证

不做命令主义(只听指令不看实际),也不做尾巴主义(谁声音大听谁的,不加专业判断)。

用 / 不用

用:

  • 需要收集多方需求或反馈并整合
  • 反馈互相矛盾,要判断听谁的、为什么
  • 方案做好了,需要带回给使用者确认再执行
  • 方案效果不佳,要回到使用者那里重新收集

不用:

  • 信息源单一且已足够精确("改第 3 行变量名")
  • 已完成多源收集,处于执行阶段

操作规程

  1. 列信息源:本次的"群众"是谁?至少两个独立来源,否则只是单方转述。
  2. 收集,先不筛:逐条记录,标来源。矛盾的意见不删,它们往往指向真问题。
  3. 集中:归类,找出一致处(可信事实)、分歧处、缺口。分歧按原因分:视角不同 / 信息不同 / 利益不同。系统化不是投票。
  4. 返回:把整理后的判断带回去。向用户说明"综合各方后我的判断是 ……,与你原始描述有出入的是 ……";只在不同读法会导致实质不同的工作时才提问。
  5. 检验:方案执行后看结果是否与判断一致;不一致时说明哪个信息源误导了判断。
  6. 再来一轮,直到没有新的重要分歧或用户确认。

先在一个具体点上深入实施取得经验,再推广:一般号召与个别指导相结合。

输出模板

信息源:[1] …… [2] …… [3] ……
一致处:……
分歧处:[A 说 …… / B 说 ……],原因:视角 / 信息 / 利益
信息缺口:……(需进一步确认)

综合各方后,我的判断是:……
依据:[源 1] + [源 2] 共同指向 ……
与用户原始描述有出入的地方:……
验证方式:……

纪律

  • 少于两个独立来源,不得宣称"综合各方"。
  • 禁止把多数意见直接当结论;少数但来自一线的深度意见要单独评估。
  • 返回环节不是走过场:分歧未处理就执行,属于命令主义。

交接

  • 分歧本质是矛盾 → contradiction-analysis
  • 判断形成后进入验证 → practice-cognition

原著依据:original-texts.md

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 Mass Line AI skill do?

群众路线:从持有真实情况的多方(用户、使用者、代码库、日志、运行结果)收集分散意见,系统化为方案,再带回去对齐与检验,循环改进。当多方意见分歧、需要汇总零散反馈、方案要拿回给真实使用者确认、或你发觉自己在闭门造车时触发;信息源单一且完整、处于执行阶段时不触发。 English: Mass line. Collect scattered input from everyone who holds ground truth (users, operators, codebase, logs, runtime results), synthesize it into a coherent plan, take it back for alignment and validation, and iterate. Trigger when inputs conflict, feedback must be consolidated, a plan needs sign-off from real users, or you sense you are designing in isolation; skip when there is a single complete source and the work is pure execution.

Why use Mass Line on TypingMind?

Because you install it once and use it with any model. Mass Line 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 Mass Line in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HughYau/qiushi-skill/tree/main/skills/mass-line. 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 Mass Line?

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 Mass Line?

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

Is the Mass Line AI skill free?

Yes. It is published on GitHub by HughYau 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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