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 CymChad/book-skill-generator --skill build-measure-learngit clone --depth 1 https://github.com/CymChad/book-skill-generatorWrote 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/cymchad/book-skill-generator/build-measure-learn)<a href="https://agentmods.dev/skills/cymchad/book-skill-generator/build-measure-learn"><img src="https://agentmods.dev/badge/skills/cymchad/book-skill-generator/build-measure-learn/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/cymchad/book-skill-generator/build-measure-learn"><img src="https://agentmods.dev/badge/skills/cymchad/book-skill-generator/build-measure-learn.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 | $0.00044 | $0.01175 |
| Opus 5 | $0.00022 | $0.00588 |
| Sonnet 5 | $0.00009 | $0.00235 |
| Haiku 4.5 | $0.00004 | $0.00118 |
Grade A, and why
build-measure-learn 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 11d 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
构建-测量-学习循环
精益创业的核心引擎。通过持续迭代的闭环,让产品持续逼近用户需求。
核心理念
快速迭代,持续学习。 精益创业的本质是"持续迭代的闭环"——构建(Build) MVP → 测量(Measure)数据 → 学习(Learn)验证假设 → 再构建优化后的产品,循环往复。
适用场景
- 想建立快速迭代的反馈循环
- 需要加速产品验证速度
- 想持续优化产品
- 希望降低开发风险
- 需要快速响应市场变化
执行步骤
步骤 1: 构建 (Build)
从想法到产品:
-
明确想法 (Idea)
- 你的核心假设是什么?
- 你想验证什么?
- 预期结果是什么?
-
开发 MVP
- 只开发验证假设必需的功能
- 使用最简单的技术实现
- 确保可以快速发布
-
快速发布
- 不要追求完美
- 尽快推向目标用户
- 收集真实数据
构建原则:
- 小批量开发
- 快速发布
- 可测量
步骤 2: 测量 (Measure)
收集和分析数据:
-
定义关键指标
- 哪些指标能验证你的假设?
- 如何衡量成功?
- 数据收集方式?
-
收集数据
- 用户行为数据
- 转化率
- 留存率
- 用户反馈
-
分析数据
- 对比预期和实际
- 识别趋势和模式
- 发现问题和机会
测量原则:
- 关注可执行指标
- 避免虚荣指标
- 使用同期群分析
- 真实用户数据
步骤 3: 学习 (Learn)
从数据中获得认知:
-
验证假设
- 假设是否成立?
- 数据是否支持你的想法?
- 有什么意外发现?
-
获得认知
- 用户真正需要什么?
- 产品哪里做得好?哪里不好?
- 下一步应该做什么?
-
做出决策
- 坚持 (Persevere): 假设成立,继续优化
- 转型 (Pivot): 假设不成立,调整方向
学习原则:
- 基于数据,而非直觉
- 关注用户行为,而非口头反馈
- 每次循环都要获得可验证的认知
步骤 4: 缩短循环周期
加速反馈循环:
- 小批量开发: 每次只开发一小部分功能
- 快速发布: 缩短从开发到发布的时间
- 自动化测试: 建立自动化测试和部署流程
- 实时数据: 实时收集和分析数据
目标:
- 缩短每次循环的时间
- 加快学习和迭代速度
- 降低试错成本
输出格式
Build-Measure-Learn 循环记录:
## 循环 #N
### Build (构建)
**想法 (Idea):**
- 核心假设:
- 预期结果:
**MVP:**
- 开发内容:
- 发布时间:
- 目标用户:
### Measure (测量)
**关键指标:**
- 指标 1: [名称] = [数值]
- 指标 2: [名称] = [数值]
- 指标 3: [名称] = [数值]
**数据收集:**
- 用户数:
- 使用率:
- 转化率:
- 留存率:
### Learn (学习)
**验证结果:**
- 假设是否成立: [是/否]
- 证据:
**关键认知:**
1. [认知 1]
2. [认知 2]
3. [认知 3]
**下一步决策:**
- [ ] 坚持 (Persevere): 继续优化
- [ ] 转型 (Pivot): 调整方向
- 转型方向(如适用):
### 循环时间
- 构建时间:
- 测量时间:
- 学习时间:
- 总循环时间:
注意事项
- 每次循环都要有明确的学习目标
- 不要跳过测量环节,凭直觉做决策
- 数据要来自真实用户,而非假设
- 循环周期越短越好
- 失败也是学习,但要快速失败
来源
本方法论来自《精益创业》(The Lean Startup) 全书核心,作者埃里克·莱斯 (Eric Ries)。
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.
- 11d ago First seen · 173 lines · 44 tokens per session scan A 96af7da4fefd
build-measure-learn is a skill published in the GitHub repository CymChad/book-skill-generator (66 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 1,175 once invoked, about $0.0002 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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