Qiushi-Skill is a collection of agent skills that turn dialectical materialist and practical philosophy into methods for investigating problems, identifying their central contradiction, testing conclusions, and continuing work. It is intended to guide AI agents through analysis and task execution. The catalogue entries are its skills, commands, hook, plugin, and agent components.
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 HughYau/qiushi-skill --skill mass-linegit clone --depth 1 https://github.com/HughYau/qiushi-skillWrote 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/hughyau/qiushi-skill/mass-line)<a href="https://agentmods.dev/skills/hughyau/qiushi-skill/mass-line"><img src="https://agentmods.dev/badge/skills/hughyau/qiushi-skill/mass-line/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/hughyau/qiushi-skill/mass-line"><img src="https://agentmods.dev/badge/skills/hughyau/qiushi-skill/mass-line.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00195 | $0.01006 |
| Opus 5 | $0.00097 | $0.00503 |
| Sonnet 5 | $0.00039 | $0.00201 |
| Haiku 4.5 | $0.00019 | $0.00101 |
Grade A, and why
mass-line 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 4d 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.
What it actually says
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》
与 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和返回验证。
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
- 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。
- 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。
- 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。
- 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。
- 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。
- 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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed · -107 lines · +92 tokens per session 5dfb49171313
- 11d ago First seen · 181 lines · 103 tokens per session scan A 499f4e22187f
mass-line is a skill published in the GitHub repository HughYau/qiushi-skill (3,773 stars, last pushed 5d ago), licensed MIT. It adds 195 tokens to every session and 1,006 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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