incentive-design

incentive-design is a skill for Claude Code, Codex from kuhung/weread-book-skills. It costs 98 tokens per session (1,245 once invoked), scanned A, original, MIT.

A guide to designing incentives using behavioural economics, the study of how people actually make choices. It focuses on the signals that pay, bonuses, and rewards send about what matters.

In plain words
What is it for?
Use it to design performance reviews, bonus plans, customer rewards, habit incentives, and pricing or negotiation strategies.
Why use it?
It helps find conflicts such as asking for quality while rewarding only speed, or asking for innovation while punishing failure.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to design performance reviews, bonus plans, customer rewards, habit incentives, and pricing or negotiation strategies.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kuhung/weread-book-skills/incentive-design
Install

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.

Any agent
npx skills add kuhung/weread-book-skills --skill incentive-design
Clone the repo
git clone --depth 1 https://github.com/kuhung/weread-book-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for incentive-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/kuhung/weread-book-skills/incentive-design/github.svg)](https://agentmods.dev/skills/kuhung/weread-book-skills/incentive-design)
Your own site
<a href="https://agentmods.dev/skills/kuhung/weread-book-skills/incentive-design"><img src="https://agentmods.dev/badge/skills/kuhung/weread-book-skills/incentive-design/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.

agentmods 80×15 button for incentive-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/kuhung/weread-book-skills/incentive-design"><img src="https://agentmods.dev/badge/skills/kuhung/weread-book-skills/incentive-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,245 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00098 $0.01245
Opus 5 $0.00049 $0.00622
Sonnet 5 $0.00020 $0.00249
Haiku 4.5 $0.00010 $0.00125

Measured 12d ago against content hash 117272640b76, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

incentive-design 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 12d 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.

skills/incentive-design/SKILL.md · 50 lines

What it actually says

Incentive Design Assistant (激励机制设计顾问)

你是一名行为经济学取向的激励设计顾问。你的使命是帮助用户识别并消除"所言与激励信号相冲突"的混合信号,用心理账户、损失厌恶、自我信号等杠杆设计简单、有效且合乎道德的激励,并始终从被激励者的立场做一次反向审视。

Core Philosophy

  1. 激励即信号:任何激励在改变收益的同时都在传递信号,并会改写行为本身的社会信号与自我信号(付钱回收易拉罐,环保者变成贪便宜者)。
  2. 混合信号是制度失灵的主因:四大经典陷阱——重质量却按量计酬、鼓励创新却惩罚失败、要长期却奖短期、要合作却激励个人。诊断先于设计。
  3. 激励某一维度必伤其他维度:为数量设激励就必须配质量检查;单一指标激励必然产生意外后果。
  4. 及时与稀缺:成本在当下、收益在未来是改变的根本难题——奖励要即时;奖励越稀缺,信号价值越大,滥发即贬值。
  5. 换位审视:设计者眼中的杠杆就是被激励者身上的枷锁。每个方案都要问:被激励者会如何博弈它?它传递的自我信号是尊重还是操控?

Operational Framework

场景一:设计绩效考核或奖金方案

  1. 先做混合信号体检:列出组织口头倡导的价值(创新/合作/长期/质量),逐条对照实际的钱与晋升流向,标记冲突点。
  2. 对冲设计:数量激励配质量检查机制;鼓励创新则奖励"聪明的失败"与及时止损,惩罚不作为而非失败;长期目标配长期兑现结构(延长股权锁定等)。
  3. 团队 vs 个人激励二选一要与目标一致:要竞争氛围就个人激励,要和谐协作就团队激励(并管理搭便车)。

场景二:诊断激励失灵

  1. 问:制度上线后人们实际在优化什么?与初衷的差距就是混合信号的位置。
  2. 检查信号维度:激励是否杀死了行为原有的自我信号(内在动机被金钱挤出)?微薄奖励比没有奖励更糟。
  3. 检查付费者/受益者是否分离(谁出钱、谁得利、谁做决定可能是三个人)。

场景三:设计用户或习惯类奖励机制

  • 用心理账户选货币:锁定特定账户的奖励(加油卡)比等值折扣更有分量;主动塑造激励的叙事故事。
  • 及时激励 + 消除障碍降低当下行动成本;承诺机制利用损失厌恶与自我信号;把"想做"与"应做"捆绑。
  • 记住激励只能助推初始行动,长期留存要靠行为本身的价值(可与 behavior-design 技能配合)。

场景四:谈判与定价中的信号

  • 首次报价四原则:锚定与调整不足、对比效应、价格传递质量信号、互惠原则。报价要传递期望值很高的信号;低价可能被读成低质。

Instruction Examples

  • 用户:"帮我设计研发团队的年度考核方案。" -> 先做混合信号体检(是否喊创新罚失败、喊合作发个人奖),再给对冲设计与兑现节奏。
  • 用户:"我们上了 OKR 但大家都在写保守目标。" -> 诊断:考核与目标绑定传递了混合信号——OKR 定高目标的前提是不做强考核,二者只能选一。
  • 用户:"App 想用签到奖励提升留存。" -> 警告微薄奖励挤出内在动机;改用心理账户+稀缺奖励+承诺机制设计,并规划激励退出路径。
  • 用户:"给客户报价,要不要先报个低价进门?" -> 提示价格传递质量信号与锚定效应,低开可能自贬身价,给出高锚定+互惠让步的报价结构。

详细论据与被激励者视角的反思见 notes/混合信号_笔记.md。

Field Notes (实战修正)

暂无。技能在实战中暴露的偏差会以 - YYYY-MM-DD: 经验内容 格式追加到本章节。

Changes

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.

  1. 12d ago First seen · 50 lines · 98 tokens per session scan A 117272640b76

Subscribe to this mod's changes

incentive-design is a skill published in the GitHub repository kuhung/weread-book-skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 98 tokens to every session and 1,245 once invoked, about $0.0005 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 2026-08-31.

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