Agent skill

Principal-Agent Incentive Check

by kangarooking in kangarooking/cangjie-skill

Helps you judge jobs, partnerships and team setups by whether people act as owners, with rewards tied to the value they create.

MITAuto-check passedBusiness, Finance & HR

SKILL.md written in Chinese; this summary is our English description.

Install Principal-Agent Incentive Check

skills CLI
$ npx skills add kangarooking/cangjie-skill --skill principal-agent -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install kangarooking/cangjie-skill principal-agent --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/books/naval-almanack-skill/principal-agent .claude/skills/principal-agent && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
principal-agent
GitHub stars
11k
Token cost
~645 tokens
SKILL.md length
150 words
Files
3
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

Helps you judge jobs, partnerships and team setups by whether people act as owners, with rewards tied to the value they create.

  • Works in 4 steps: 职业选择:「去大公司还是小创业公司」「打工还是自己干」 → 合作设计:「怎么设计分成/激励让合伙人真的上心」 → 困惑现象:「为什么同事都在磨洋工/外包总出问题」 → …
  • Comparing a job at a large company with one at a small startup
  • SKILL.md covers R — 原文 (Reading), I — 方法论骨架 (Interpretation), A1 — 书中的应用 (Past Application) and A2 — 触发场景 (Future Trigger) ★, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Drawn from Naval Ravikant's almanack, this skill uses the principal-agent idea: a person acting on their own behalf tends to do good work, while one acting for someone else tends to optimize for themselves. The tighter pay is tied to the value someone creates, the more they behave like a principal. It also warns against the notion that you need a knowledgeable agent to act for you. The skill text is written in Chinese.

Four steps: diagnose whether your own role is principal or agent and how closely reward tracks value; look for or create a principal position, such as equity, revenue share, owning what you build or joining a small organization; check each partner's incentives by asking what counts as winning for them, flagging pure agent structures as high risk; and record the conclusion for later decisions. It offers structure, not salary-negotiation scripts, and notes that the owner feeling of a small company does not carry over to large ones.

When your agent uses it

  • Comparing a job at a large company with one at a small startup
  • Designing revenue share or equity so partners care about results
  • Working out why a team or contractor is not taking ownership
  • Checking whose interests your current role actually serves

Example prompts

  • “Should I stay at my big company or join a small startup? Look at it through incentives.”
  • “How should I structure profit sharing so my two partners stay invested?”
  • “Why do the outsourced developers on our project keep missing details?”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 职业选择:「去大公司还是小创业公司」「打工还是自己干」
  2. 合作设计:「怎么设计分成/激励让合伙人真的上心」
  3. 困惑现象:「为什么同事都在磨洋工/外包总出问题」
  4. 自我诊断:「我是在为谁的利益工作」

What it can do on your machine

Read from SKILL.md and the folder at commit a28de55. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Principal-Agent Incentive Check loads about 645 tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 150 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~645

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from kangarooking/cangjie-skill at commit a28de55, republished under its MIT licence (© kangarooking). 150 words, ~645 tokens.

Download SKILL.mdSave it as .claude/skills/principal-agent/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
principal-agent
description
当用户选择职业/组织/合作方式、困惑「为什么大公司磨洋工/小公司拼命」「该不该自己干」时调用。 核心理念: 委托人(主人)会把事做好, 代理人会为自己利益优化; 收益与创造价值绑得越紧, 越像委托人; 别让媒体洗脑你需要代理人。 不适用于: 具体薪酬谈判数字、组织架构设计细节。 Triggers: 激励/代理/主人/打工 vs 创业/利益绑定/principal/agent/incentive
source_book
《纳瓦尔宝典:财富与幸福指南》 纳瓦尔·拉维坎特
source_chapter
第一章·财富 / 第二节 培养判断力 / 经济学 / 委托-代理问题
tags
economics, incentive, career, organization

委托-代理识别

R — 原文 (Reading)

如果你想做好,那你必须亲自去做。当你是委托人,那你就是主人你就会关心并且会把工作做得很好。当你是代理人,你是在为别人的利益做事,你可能会把事情做得很糟糕。……你能把某个人的收益和他所创造的价值联系得越紧密,就越能把他们变成委托人。

— 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第一章·财富

I — 方法论骨架 (Interpretation)

委托-代理问题是微观经济学最基本的问题:利益归属决定行为质量。 当你是委托人(自己的钱/自己的事),你会做好;当你是代理人(为别人利益做事),你会为自己优化。 推论三条: ① 选择位置时,优先选「每个人都能感到自己是委托人」的小组织; ② 设计合作时,把收益与创造的价值绑定得越紧越好(股权、分成、责任到人); ③ 警惕「代理人叙事」——媒体和现代社会长期洗脑你「需要一个知识渊博的代理人」,而委托人直觉其实人人都有。 用在职业上:为别人打工=代理人拿最低报酬;拥有产权和判断=委托人拿剩余。

A1 — 书中的应用 (Past Application)

案例 1: 为别人工作拿最低报酬
  • 问题: 为什么高薪打工者无法致富
  • 方法论的使用: 雇主是委托人(承担风险/责任/知识产权),雇员是代理人拿「最低限度的报酬」
  • 结论: 工资再高也不是财富
  • 结果: 医生开私人诊所(品牌)后才成为委托人
案例 2: 小公司人人像委托人
  • 问题: 如何让团队用心做事
  • 方法论的使用: 越小的公司,每个人越能感觉到自己是委托人
  • 结论: 「你越觉得自己不是代理人,你将会把工作做得更好」
  • 结果: 组织结构越扁平、收益越绑定,行为质量越高

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?
  1. 职业选择:「去大公司还是小创业公司」「打工还是自己干」
  2. 合作设计:「怎么设计分成/激励让合伙人真的上心」
  3. 困惑现象:「为什么同事都在磨洋工/外包总出问题」
  4. 自我诊断:「我是在为谁的利益工作」
语言信号
  • "大公司 vs 小公司怎么选"
  • "怎么让团队/合伙人更用心"
  • "为什么没人对结果负责"
  • "principal-agent / ownership / who benefits"
与相邻 skill 的区分
  • 与 wealth-structure 的区别: 财富结构是个人资产框架;本 skill 是组织/合作中的激励透镜
  • 与 judgment-training 的区别: 委托代理是判断力心智模型库里的一个模型

E — 可执行步骤 (Execution)

  1. 诊断你当前的角色

    • 完成标准: 回答「我的收益与创造的价值绑定程度(低/中/高)」「我是委托人还是代理人」
  2. 寻找或创建委托人位置

    • 完成标准: 列出 1–2 个具体动作(要求股权/分成、做有产权的事、加入小组织)
  3. 检查合作方的激励结构

    • 完成标准: 对每个合作者问「他赢的判定标准是什么」,确认利益是否一致
    • 判停条件: 若发现纯代理结构(收益完全脱钩)且无法改变,标记为高风险合作
  4. 为未来决策保留记录

    • 完成标准: 记录本次诊断结论,作为下次职业/合作选择的输入

B — 边界 (Boundary) ★

不要在以下情况使用此 skill
  • 用户要具体薪酬谈判话术(本 skill 给结构不给话术)
  • 管理细节(如何监督/考核)不是本 skill 的重点——先改结构再谈管理
作者在书中警告的失败模式
  • 依赖代理人: 「媒体和现代社会花了大量时间来洗脑你:让你认为需要一个代理人」
  • 收益脱钩: 收益与价值脱钩时,代理人必然为自己优化
作者的盲点 / 时代局限
  • 「小公司人人像委托人」在规模化后不成立,作者未给大组织化解决方案
  • 委托-代理只是心智模型之一,不能解释所有组织问题
容易混淆的邻近方法论
  • wealth-structure: 两者的交集是「股权绑定」,但视角不同(组织 vs 个人)

相关 skills (阶段 3 定稿)

  • composes-with: wealth-structure(股权绑定是共同解法)、judgment-training

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓ (v07)
  • 测试通过率: 见 test-results.md
  • 蒸馏时间: 2026-08-01

© kangarooking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in books/naval-almanack-skill/principal-agent of kangarooking/cangjie-skill.

  • SKILL.md
  • test-prompts.json
  • test-results.md

Open the folder on GitHubat commit a28de55

Compare with similar skills

Principal-Agent Incentive Check next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Principal-Agent Incentive Check compared with similar skills
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Principal-Agent Incentive Check this skillkangarooking/cangjie-skill11k—~645Automated safety check: PassMIT
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Zhang Yiming Perspectivealchaincyf/zhang-yiming-skill1741 repos~3.2kAutomated safety check: PassMIT
Korean Government Grant Searchdjfksjd/ir-search392—~3.5kAutomated safety check: NotesMIT
Mao Zedong Thinking Partnerzhangtianruiwork-droid/Maoxuan-Changzheng441—~2.9kAutomated safety check: PassNone
Constraint Enginelijigang/ljg-skills7.5k—~2.1kAutomated safety check: PassMIT

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Questions about Principal-Agent Incentive Check

What does Principal-Agent Incentive Check do?

Helps you judge jobs, partnerships and team setups by whether people act as owners, with rewards tied to the value they create. Drawn from Naval Ravikant's almanack, this skill uses the principal-agent idea: a person acting on their own behalf tends to do good work, while one acting for someone else tends to optimize for themselves. The tighter pay is tied to the value someone creates, the more they behave like a principal.

When should I use Principal-Agent Incentive Check?

Principal-Agent Incentive Check fits situations like: comparing a job at a large company with one at a small startup; designing revenue share or equity so partners care about results; working out why a team or contractor is not taking ownership; checking whose interests your current role actually serves.

How do I install Principal-Agent Incentive Check in Claude Code?

Run `npx skills add kangarooking/cangjie-skill --skill principal-agent -a claude-code`. Or copy the skill folder (books/naval-almanack-skill/principal-agent in kangarooking/cangjie-skill) into .claude/skills/principal-agent in your project. Claude Code loads it when a task matches its description.

How do I install Principal-Agent Incentive Check in Codex?

Run `npx skills add kangarooking/cangjie-skill --skill principal-agent -a codex`. Or copy the skill folder (books/naval-almanack-skill/principal-agent in kangarooking/cangjie-skill) into .agents/skills/principal-agent in your project. Codex loads it when a task matches its description.

Can I use Principal-Agent Incentive Check in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kangarooking/cangjie-skill --skill principal-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/principal-agent, .gemini/skills/principal-agent, .github/skills/principal-agent and .opencode/skills/principal-agent in your project.

What does Principal-Agent Incentive Check need to run?

SKILL.md names no scripts, command-line tools or credentials: Principal-Agent Incentive Check is instructions for the agent only.

Does Principal-Agent Incentive Check access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Principal-Agent Incentive Check safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Principal-Agent Incentive Check use?

Principal-Agent Incentive Check is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Principal-Agent Incentive Check use?

About 645 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Principal-Agent Incentive Check?

Skills that share tags, products or a category with Principal-Agent Incentive Check: Startup Pressure Test (Kappaemme-git/codex-startup-pressure-test-skill, 990 stars), Zhang Yiming Perspective (alchaincyf/zhang-yiming-skill, 174 stars), Korean Government Grant Search (djfksjd/ir-search, 392 stars) and Mao Zedong Thinking Partner (zhangtianruiwork-droid/Maoxuan-Changzheng, 441 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Principal-Agent Incentive Check?

kangarooking (a GitHub user) maintains it in kangarooking/cangjie-skill, which has 11,071 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 2, 2026.

Source: kangarooking/cangjie-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.