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 ace3000chao/book2startup --skill positive-interaction-ratiogit clone --depth 1 https://github.com/ace3000chao/book2startupWrote 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/ace3000chao/book2startup/positive-interaction-ratio)<a href="https://agentmods.dev/skills/ace3000chao/book2startup/positive-interaction-ratio"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/positive-interaction-ratio/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/ace3000chao/book2startup/positive-interaction-ratio"><img src="https://agentmods.dev/badge/skills/ace3000chao/book2startup/positive-interaction-ratio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00152 | $0.02203 |
| Opus 5 | $0.00076 | $0.01102 |
| Sonnet 5 | $0.00030 | $0.00441 |
| Haiku 4.5 | $0.00015 | $0.00220 |
Grade A, and why
positive-interaction-ratio 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3:1 Positive Interaction Ratio（正向互动比率）
R — 原文 (Reading)
"For people to be happy and productive at work, they need to experience positive interactions (appreciation, praise) vs. negative (reprimands, criticism) with their manager in a ratio of at least 3:1."
— Verne Harnish, Scaling Up (第5章 Managers)
翻译： 要让人在工作中感到快乐且高效，他们与上级的正向互动（认可、表扬）vs. 负向互动（批评、指责）比例需要至少达到3:1。
I — 方法论骨架 (Interpretation)
- 核心原则： 管理者的日常互动质量决定团队情绪底色。每一次批评、指令、纠错都是"负向互动"，每一次认可、感谢、鼓励都是"正向互动"。
- 比例阈值： 3:1是"最低健康线"，低于此比例团队开始进入"防守模式"——员工不愿主动承担、不愿汇报问题、不愿冒险创新。
- 为什么重要： 人类大脑对负面威胁的反应比对正面奖励强5倍（负面偏差），所以管理者必须刻意积累正向互动来对冲天然的负向倾向。
- 不是讨好： 正向互动不等于"好好先生"——真诚的认可 + 建设性的纠错，比例对就行。
- 情境差异： 新人需要更多正向互动建立安全感；高绩效者需要更多挑战性互动而非廉价表扬。
- 测量方法： Harnish建议用"一周互动日志"记录正向和负向互动次数，至少坚持2周才能看到真实比例。
A1 — 书中的应用 (Past Application)
案例 1: 管理者是天生的"灭火队员"
- 问题: 大多数管理者因为日常"救火"，自然形成低正向比率——他们只有在出问题才找员工谈。
- 方法论的使用: Harnish让管理者记录一周内所有与每个下属的互动，结果大多数人的比率是1:1甚至0.5:1。
- 结论: 低比率不是"态度问题"，而是"习惯问题"——管理者没有刻意建立正向互动机制。
- 结果: 通过刻意练习，管理者能在4-6周内将比率提升到3:1以上，团队敬业度显著提升。
案例 2: 表扬需要具体，否则是"敷衍"
- 问题: 泛泛的"你做得不错"不计入正向互动——员工知道这是客套话。
- 方法论的使用: 有效的正向互动必须是具体的："你在X客户项目中提前2天交付，而且客户满意度达到95分，这个结果对Q3目标很关键。"
- 结论: 真诚的具体认可比泛泛表扬更有力量，且不会被当作"拍马屁"。
- 结果: 具体表扬后，员工更清楚什么是值得复制的行为，下一次绩效改进方向更清晰。
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 1:1沟通变成诉苦会：每次1:1员工都在抱怨，老板疲于应付，但问题没有结构性解决。
- 团队士气持续低迷：员工不主动发言、不愿承担新项目、离职率莫名上升。
- 批评后无改进：你指出问题，员工当时点头，但下次同样的问题继续出现。
- 员工汇报"感受不到被认可"：离职面谈或匿名调研中出现这类反馈。
- 管理者自我感觉良好但团队数据差：管理者认为"我人很好"，但敬业度分数、目标达成率、离职率都在恶化。
语言信号 (用户的话里出现这些就应激活)
- "我跟他们说了很多次了，就是不改"
- "现在的年轻员工太玻璃心，批评不得"
- "我不知道怎么夸人，总觉得做得好是应该的"
- "团队氛围很沉闷，开会没人发言"
- "员工总说感受不到认可"
与相邻 skill 的区分
- 与
dont-demotivate-dehassle的区别：去障碍是"消除外部阻力"，正向比率是"建立内在动力"；先去障碍，再谈激励。 - 与
coaching-top-performers的区别：一流教练关注绩效提升技术，正向比率关注关系质量，两者都是管理者的必修课。
E — 可执行步骤 (Execution)
- 审计当前比率（1-2周）
- 记录每天与每个下属的所有互动，标记"正向"或"负向"
- 正向：具体表扬、认可、感谢、建设性鼓励
- 负向：批评、纠错、指令、负面反馈
- 完成标准：获得真实比率数据（大多数人会惊讶于自己的低比率）
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.
- 9d ago First seen · 139 lines · 152 tokens per session scan A a2e911decb73
positive-interaction-ratio is a skill published in the GitHub repository ace3000chao/book2startup (80 stars, last pushed 4mo ago), licensed MIT. It adds 152 tokens to every session and 2,203 once invoked, about $0.0008 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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