Cost Accounting

Community

kangarooking

cost-accounting

当用户需要把产品价格"拆解"成小额日常消费来降低价格抵触时调用此 skill。适用场景：耐用消费品（家电、家具、课程）消费者觉得一次性支出太高、节能型产品需要展示长期节省、增量产品需要让额外花费显得微不足道。不适用于：低价一次性消费品（无需拆解）、冲动消费品类（算账反而破坏氛围）。关键 trigger 信号：用户提到"嫌贵""怎么降低价格感知""每天才多少钱""长期划算"。两种核心方法：平摊法（高价品除以使用天数）和省钱法（算出长期使用节省的金额）。

Overview

Publisher	kangarooking
Repository	`viral-copywriting-skill`
Skill name	`cost-accounting`
Stars	80
Forks	12
Bundled files	1
License	MIT
Links	Skill source Repository

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 kangarooking on GitHub. Read the source before you install it.

Installation

Install the Cost Accounting AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/kangarooking/viral-copywriting-skill/tree/main/cost-accounting
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.

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/kangarooking/viral-copywriting-skill.git /tmp/viral-copywriting-skill
mkdir -p .claude/skills
cp -r /tmp/viral-copywriting-skill/cost-accounting .claude/skills/cost-accounting

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cost Accounting 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 Cost Accounting 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 Cost Accounting 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.

算账说服法

R — 原文 (Reading)

当读者觉得产品有点贵时，你可以帮他算一笔账，把总价拆解成每一天、每一次的费用，让他发现"原来也没那么贵"。关键是平摊后要跟一个消费者熟悉的、小额的日常消费做对比——"每天只要1.5元，比一瓶矿泉水还便宜"。

— 关健明, 第三章 3.2

I — 方法论骨架 (Interpretation)

算账说服法的核心逻辑：通过重新框定价格，改变消费者的价格感知。

方法一：平摊法（适用于耐用高价品）

确定使用周期: 估算产品的合理使用寿命（如5年、10年、365次）。
计算日均/次均成本: 将总价除以使用天数或次数。
对比熟悉的小额消费: 找到消费者日常花钱的、金额相近的项目做对比（一瓶水、一包纸巾、一顿早餐）。

方法二：省钱法（适用于节能/替代型产品）

算出每次使用的节省额: 与传统方案对比，算出每次使用省多少钱。
乘以使用频率得出年省额: 每次省X元 x 每年用Y次 = 每年省Z元。
展示长期节省: 把年省额放大到产品使用寿命周期内的总节省额。

关键原则：算账的结论必须让消费者觉得"这点钱不算什么"——通过对比一个熟悉的小额消费来强化这个感受。

A1 — 书中的应用 (Past Application)

案例 1: 洗碗机 2800元

问题: 一台洗碗机售价2800元，消费者觉得"花2800元买个洗碗机太奢侈了"。
方法论的使用: 平摊法——2800元 ÷ 5年（合理使用寿命）÷ 365天 = 约1.5元/天。然后对比熟悉消费："每天1.5元，比一瓶矿泉水还便宜，却能帮你每天省下30分钟洗碗时间"。
结论: 从"一次性花2800元"变成"每天只花1.5元"，价格感知发生质变。
结果: 消费者从"太贵了"转变为"一天才1块5，太值了"。

案例 2: 生态大米增量成本

问题: 生态大米比普通大米每斤贵5元，消费者觉得溢价太高。
方法论的使用: 算增量成本——一个家庭每月吃20斤大米，每斤贵5元，每月多花100元。然后对比："每月多花100元，不到一次外卖的钱，全家人就能吃到真正安全的有机大米"。
结论: 把"每斤贵5元"（相对溢价高）转化为"每月多花100元"（绝对值可接受），再对比一次外卖（熟悉消费），让溢价显得微不足道。
结果: 增量成本的感知大幅降低，转化率提升。

案例 3: 净水器节水

问题: 净水器虽然价格不高，但消费者担心后续使用成本（滤芯更换、废水排放）。
方法论的使用: 省钱法——与传统桶装水对比：桶装水每桶15元，每月4桶 = 60元/月 = 720元/年。净水器滤芯每年更换费用仅200元，每年省520元。3年省1560元，相当于净水器本身的价格。
结论: 通过省钱法，净水器从"又要花钱"变成"用着用着就回本了"。
结果: 消费者的关注点从购买成本转向使用节省，购买决策更容易做出。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

产品客单价较高，消费者犹豫不决，需要降低心理门槛。
产品比同类产品贵，需要让消费者理解"多花的钱其实很少"。
节能/环保产品需要展示长期经济效益。
订阅制/年费制产品需要让消费者觉得"每天才几块钱"。
增量产品（升级款、高配款）需要让差价显得微不足道。

语言信号

"消费者嫌贵，怎么让他们觉得不贵？"
"帮用户算一笔账"
"每天才几块钱"
"长期来看更划算"
"怎么把价格拆解到每一天？"
"怎么展示产品的省钱效果？"

与相邻 skill 的区分

与 price-anchor 的区别: price-anchor 通过与更高价的参照物对比来制造划算感，cost-accounting 通过自身价格的拆解来降低感知。前者是"跟别人比"，后者是"自己算账"。两者可以组合使用：先锚定再算账，双重降低价格抵触。
与 customer-testimonial 的区别: customer-testimonial 用用户口碑建立信任，cost-accounting 用数学逻辑降低价格感知。前者解决"信不信"的问题，后者解决"贵不贵"的问题。

E — 可执行步骤 (Execution)

判断使用哪种方法
- 完成标准: 确认产品类型。耐用高价品（家电、家具、课程）→ 平摊法；节能/替代型产品（净水器、LED灯、节能设备）→ 省钱法；增量产品（升级款）→ 增量平摊法。
平摊法——确定使用周期和日均成本
- 完成标准: 写出产品的合理使用寿命（年/月/天/次数），用总价除以使用总数得出日均或次均成本。数字必须合理，不能夸大使用周期。
平摊法——找到对比消费
- 完成标准: 找到一个消费者每天都花钱的、金额与日均成本相近的项目。公式："每天只要[X元]，相当于[熟悉小额消费]，比[某物]还便宜"。
省钱法——计算每次节省和年省额
- 完成标准: 与传统方案做精确对比，算出每次使用的节省金额，乘以年使用频率得出年省额。数字必须基于真实数据。
省钱法——展示长期节省
- 完成标准: 展示产品使用寿命周期内的总节省额，最好超过产品本身的价格（"省下来的钱够再买一台"）。
最终检查
- 完成标准: 确认：(1) 使用周期估算合理不夸大；(2) 对比消费是目标消费者真正熟悉的日常支出；(3) 计算逻辑清晰，消费者能一眼看懂；(4) 结论确实能让人产生"这点钱不算什么"的感受。

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

低价一次性消费品（如零食、纸巾），算账反而让人觉得你在小题大做。
冲动消费/情感消费品类（如鲜花、巧克力），理性算账破坏购买情绪。
产品使用周期不确定或很短（算出的日均成本不低，反而暴露"其实挺贵"）。
目标消费者是高收入群体（他们对小额价格不敏感，算账显得掉价）。

作者在书中警告的失败模式

夸大使用周期: 为了降低日均成本，把5年寿命的产品说成10年，消费者不傻，过度夸大会降低信任。
对比消费不熟悉: "每天1.5元，相当于半个包子"——消费者对"半个包子"没有消费感知。必须选消费者每天都在花钱的项目。
计算逻辑复杂: 算账超过两步，消费者就懒得看了。"总价÷天数=日均"一步到位最好。
算出来的数字还是不低: 平摊后日均10元以上，对比什么都显得不便宜，说明产品定价本身确实超出了消费者的心理阈值。

作者的盲点 / 时代局限

2017年后，消费者对"每天只需X元"的话术已有一定免疫力（保险、课程等行业过度使用），需要更多创意来避免"套路感"。
未讨论会员制/订阅制场景的算账策略——如"年费299，相当于每月24.9"在SaaS和内容平台中已非常常见。
未涉及"隐形消费"的算账——如智能设备的后续服务费、滤芯耗材成本等，消费者越来越关注总体拥有成本而非单次购买价格。

审计信息

验证通过: V1 ✓ / V2 ✓ / V3 ✓
测试通过率: 待测
蒸馏时间: 2026-05-02

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

test-prompts.json2 KB

Frequently asked questions

What does the Cost Accounting AI skill do?

Why use Cost Accounting on TypingMind?

Because you install it once and use it with any model. Cost Accounting 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 Cost Accounting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kangarooking/viral-copywriting-skill/tree/main/cost-accounting. 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 Cost Accounting?

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 Cost Accounting?

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

Is the Cost Accounting AI skill free?

Yes. It is published on GitHub by kangarooking 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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Overview