chokcoco/teach-yourself-skill

> 基于当前 Skill 生成的单个完整课程参考：[如何实现高质量的 AI Code Review](https://chokcoco.github.io/courses/high-quality-ai-code-review/index.html)

可通过 [skills](https://github.com/vercel-labs/skills) CLI 直接从 GitHub 安装：

中文学生可见文本需要通过 [Humanizer-zh](https://github.com/op7418/Humanizer-zh) 的语言质量闸门。Skill 系统目前没有可在 frontmatter 中声明并自动安装另一个 Skill 的通用机制；因此本仓库将它作为**显式运行时依赖**写入 [依赖说明](references/humanizer-dependency.md) 和 `SKILL.md`。

获取或安装 `humanizer-zh`： [op7418/Humanizer-zh](https://github.com/op7418/Humanizer-zh)。

2. 读取目标课程 workspace 中已有的 `MISSION.md`、`RESOURCES.md`、`COURSE-GENERATION-SPEC.md`、`COURSE-BLUEPRINT.md` 和 `NOTES.md`。 3. 读取目标目录已有的生成脚本、课程目录、样章、参考资料和质量报告。不要覆盖用户改动。 4. 生成或改写中文学生可见文本前，完整读取已安装的 [Humanizer-zh](https://github.com/op7418/Humanizer-

3. 读取目标目录已有的生成脚本、课程目录、样章、参考资料和质量报告。不要覆盖用户改动。 4. 生成或改写中文学生可见文本前，完整读取已安装的 [Humanizer-zh](https://github.com/op7418/Humanizer-zh) 的 `humanizer-zh/SKILL.md`，并执行本文的 Humanizer 闸门。安装约定见 [humanizer 依赖](references/humanizer-dependency.md)。 5. 进入第二阶段

4. 生成或改写中文学生可见文本前，完整读取已安装的 [Humanizer-zh](https://github.com/op7418/Humanizer-zh) 的 `humanizer-zh/SKILL.md`，并执行本文的 Humanizer 闸门。安装约定见 [humanizer 依赖](references/humanizer-dependency.md)。

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Executable file

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Executable file

<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.x

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">

<p>下一章：<a href="./02-model-agent-loop-and-harness.md">模型、agent loop 与 harness</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/zh-Hans-CN/index/harness-en

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/zh-Hans-CN/index/harness-engineering/" target="_blank" rel="noreferrer">工程技术：在智能体优先的世界中利用 Codex</a>. OpenAI, 2026-02-11.</li><li>Ryan Lopopolo. <a href="https://open

<ul><li>Ryan Lopopolo. <a href="https://openai.com/zh-Hans-CN/index/harness-engineering/" target="_blank" rel="noreferrer">工程技术：在智能体优先的世界中利用 Codex</a>. OpenAI, 2026-02-11.</li><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-eng

- Ryan Lopopolo. [工程技术：在智能体优先的世界中利用 Codex](https://openai.com/zh-Hans-CN/index/harness-engineering/). OpenAI, 2026-02-11.

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

<p>上一章：<a href="./01-what-harness-engineering-changes.md">Harness Engineering 到底改变了什么？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Michael Bolin. <a href="https://openai.com/index/unrolling-th

<h2 id="参考文献">参考文献</h2> <ul><li>Michael Bolin. <a href="https://openai.com/index/unrolling-the-codex-agent-loop/" target="_blank" rel="noreferrer">Unrolling the Codex agent loop</a>. OpenAI, 2026-01-23.</li><li>Celia Chen. <a href="https://

<ul><li>Michael Bolin. <a href="https://openai.com/index/unrolling-the-codex-agent-loop/" target="_blank" rel="noreferrer">Unrolling the Codex agent loop</a>. OpenAI, 2026-01-23.</li><li>Celia Chen. <a href="https://openai.com/index/unlocki

- Michael Bolin. [Unrolling the Codex agent loop](https://openai.com/index/unrolling-the-codex-agent-loop/). OpenAI, 2026-01-23.

- Celia Chen. [Unlocking the Codex harness: how we built the App Server](https://openai.com/index/unlocking-the-codex-harness/). OpenAI, 2026-02-04.

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

<p>上一章：<a href="./02-model-agent-loop-and-harness.md">模型、agent loop 与 harness</a><br> 下一章：<a href="./04-agent-legible-repository.md">智能体怎样读懂项目？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>OpenAI. <

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>OpenAI. <a href="https://openai.c

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- OpenAI. [How evals drive the next chapter in AI for businesses](https://openai.com/index/evals-drive-next-chapter-of-ai/). 2025-11-19.

- Shopify Developers. [DiscountCombinesWith](https://shopify.dev/docs/api/admin-graphql/latest/objects/DiscountCombinesWith). 访问于 2026-07-10.

<p>上一章：<a href="./03-verifiable-intent-contract.md">怎样把“帮我做完”写成可验证意图？</a><br> 下一章：<a href="./05-retrofit-existing-enterprise-repository.md">怎样改造一个已有企业仓库？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <u

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>matklad. 

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>matklad. <a href="https://matklad

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- matklad. [ARCHITECTURE.md](https://matklad.github.io/2021/02/06/ARCHITECTURE.md.html). 2021-02-06.

- [AGENTS.md open format](https://agents.md/). 访问于 2026-07-10.

<p>上一章：<a href="./04-agent-legible-repository.md">智能体怎样读懂项目？</a><br> 下一章：<a href="./06-build-agent-first-repository.md">怎样从零建设 agent-first 新仓库？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Shopify D

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Shopify Developers. <a href="http

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- Shopify Developers. [DiscountCombinesWith](https://shopify.dev/docs/api/admin-graphql/latest/objects/DiscountCombinesWith). 访问于 2026-07-10.

- Shopify Developers. [Discount Function support for rejecting discount codes](https://shopify.dev/changelog/discount-rejection-support-for-discount-functions). 2025-12-17.

<p>上一章：<a href="./05-retrofit-existing-enterprise-repository.md">怎样改造一个已有企业仓库？</a><br> 下一章：<a href="./07-tools-for-reliable-action.md">什么工具能让智能体真正行动？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><l

<h2 id="参考文献">参考文献</h2> <ul><li>React Team. <a href="https://react.dev/blog/2025/10/01/react-19-2" target="_blank" rel="noreferrer">React 19.2</a>. 2025-10-01.</li><li>Vite Team. <a href="https://vite.dev/blog/announcing-vite8-1" target="_b

<ul><li>React Team. <a href="https://react.dev/blog/2025/10/01/react-19-2" target="_blank" rel="noreferrer">React 19.2</a>. 2025-10-01.</li><li>Vite Team. <a href="https://vite.dev/blog/announcing-vite8-1" target="_blank" rel="noreferrer">V

- React Team. [React 19.2](https://react.dev/blog/2025/10/01/react-19-2). 2025-10-01.

- Vite Team. [Vite 8.1 is out](https://vite.dev/blog/announcing-vite8-1). 2026-06-23.

- Spring. [Spring Boot CLI and stable versions](https://docs.spring.io/spring-boot/cli/). 访问于 2026-07-10.

- Shopify Engineering. [We replaced Redis with MySQL for inventory reservations—and it scaled](https://shopify.engineering/scaling-inventory-reservations). 2026-05-12.

<p>上一章：<a href="./06-build-agent-first-repository.md">怎样从零建设 agent-first 新仓库？</a><br> 下一章：<a href="./08-guardrails-permissions-and-approval.md">怎样让智能体有自由但不越界？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h

<h2 id="参考文献">参考文献</h2> <ul><li>Celia Chen. <a href="https://openai.com/index/unlocking-the-codex-harness/" target="_blank" rel="noreferrer">Unlocking the Codex harness: how we built the App Server</a>. OpenAI, 2026-02-04.</li><li>Brandur L

<ul><li>Celia Chen. <a href="https://openai.com/index/unlocking-the-codex-harness/" target="_blank" rel="noreferrer">Unlocking the Codex harness: how we built the App Server</a>. OpenAI, 2026-02-04.</li><li>Brandur Leach. <a href="https://s

- Celia Chen. [Unlocking the Codex harness: how we built the App Server](https://openai.com/index/unlocking-the-codex-harness/). OpenAI, 2026-02-04.

- Brandur Leach. [Designing robust and predictable APIs with idempotency](https://stripe.com/blog/idempotency). Stripe, 2017-02-22.

- Malcolm Featonby. [Making retries safe with idempotent APIs](https://aws.amazon.com/builders-library/making-retries-safe-with-idempotent-APIs/). Amazon Builders' Library.

<p>上一章：<a href="./07-tools-for-reliable-action.md">什么工具能让智能体真正行动？</a><br> 下一章：<a href="./09-evals-feedback-and-observability.md">如何知道它真的做对了？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lo

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>GitHub. <

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>GitHub. <a href="https://docs.git

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- GitHub. [About hooks for GitHub Copilot agents](https://docs.github.com/en/copilot/concepts/agents/hooks). 访问于 2026-07-10.

- Alexis King. [Parse, don't validate](https://lexi-lambda.github.io/blog/2019/11/05/parse-don-t-validate/). 2019-11-05.

<p>上一章：<a href="./08-guardrails-permissions-and-approval.md">怎样让智能体有自由但不越界？</a><br> 下一章：<a href="./10-long-running-state-and-recovery.md">任务跑几小时，怎样不失忆？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul>

<h2 id="参考文献">参考文献</h2> <ul><li>OpenAI. <a href="https://openai.com/index/evals-drive-next-chapter-of-ai/" target="_blank" rel="noreferrer">How evals drive the next chapter in AI for businesses</a>. 2025-11-19.</li><li>Anthropic. <a href="h

<ul><li>OpenAI. <a href="https://openai.com/index/evals-drive-next-chapter-of-ai/" target="_blank" rel="noreferrer">How evals drive the next chapter in AI for businesses</a>. 2025-11-19.</li><li>Anthropic. <a href="https://www.anthropic.com

- OpenAI. [How evals drive the next chapter in AI for businesses](https://openai.com/index/evals-drive-next-chapter-of-ai/). 2025-11-19.

- Anthropic. [Demystifying evals for AI agents](https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents). 2026-01-09.

- Shopify Engineering. [We replaced Redis with MySQL for inventory reservations—and it scaled](https://shopify.engineering/scaling-inventory-reservations). 2026-05-12.

<p>上一章：<a href="./09-evals-feedback-and-observability.md">如何知道它真的做对了？</a><br> 下一章：<a href="./11-autonomy-and-orchestration.md">何时提高自治，何时交给人？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Anthrop

<h2 id="参考文献">参考文献</h2> <ul><li>Anthropic. <a href="https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents" target="_blank" rel="noreferrer">Effective harnesses for long-running agents</a>. 2025-11-26.</li><li>Ope

<ul><li>Anthropic. <a href="https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents" target="_blank" rel="noreferrer">Effective harnesses for long-running agents</a>. 2025-11-26.</li><li>OpenAI. <a href="https://de

- Anthropic. [Effective harnesses for long-running agents](https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents). 2025-11-26.

- OpenAI. [Run long horizon tasks with Codex](https://developers.openai.com/blog/run-long-horizon-tasks-with-codex). 2026-02-23.

- Michael Bolin. [Unrolling the Codex agent loop](https://openai.com/index/unrolling-the-codex-agent-loop/). OpenAI, 2026-01-23.

- Brandur Leach. [Designing robust and predictable APIs with idempotency](https://stripe.com/blog/idempotency). Stripe, 2017-02-22.

<p>上一章：<a href="./10-long-running-state-and-recovery.md">任务跑几小时，怎样不失忆？</a><br> 下一章：<a href="./12-governance-drift-security-and-cost.md">速度提高后，怎样控制漂移和风险？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul

<h2 id="参考文献">参考文献</h2> <ul><li>OpenAI. <a href="https://openai.com/index/open-source-codex-orchestration-symphony/" target="_blank" rel="noreferrer">An open-source spec for Codex orchestration: Symphony</a>. 2026-04-27.</li><li>Anthropic. 

<ul><li>OpenAI. <a href="https://openai.com/index/open-source-codex-orchestration-symphony/" target="_blank" rel="noreferrer">An open-source spec for Codex orchestration: Symphony</a>. 2026-04-27.</li><li>Anthropic. <a href="https://www.ant

- OpenAI. [An open-source spec for Codex orchestration: Symphony](https://openai.com/index/open-source-codex-orchestration-symphony/). 2026-04-27.

- Anthropic. [Scaling managed agents: decoupling the brain from the hands](https://www.anthropic.com/engineering/managed-agents). 2026-04-08.

- Anthropic. [Building a C compiler with a team of parallel Claudes](https://www.anthropic.com/engineering/building-c-compiler). 2026-02-05.

<p>上一章：<a href="./11-autonomy-and-orchestration.md">何时提高自治，何时交给人？</a><br> 下一章：<a href="./13-capstone-apply-harness.md">怎样把 Harness 用到自己的仓库？</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lop

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Anthropic

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Anthropic. <a href="https://www.a

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- Anthropic. [An update on recent Claude Code quality reports](https://www.anthropic.com/engineering/april-23-postmortem). 2026-04-23.

- METR. [Task-completion time horizons of frontier AI models](https://metr.org/time-horizons/). 更新于 2026-05-08.

- GitHub. [About hooks for GitHub Copilot agents](https://docs.github.com/en/copilot/concepts/agents/hooks). 访问于 2026-07-10.

<p>上一章：<a href="./12-governance-drift-security-and-cost.md">速度提高后，怎样控制漂移和风险？</a><br> 返回：<a href="../index.html">课程目录</a><br> 术语复习：<a href="../reference/glossary.md">术语表</a></p> <h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https:/

<h2 id="参考文献">参考文献</h2> <ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Anthropic

<ul><li>Ryan Lopopolo. <a href="https://openai.com/index/harness-engineering/" target="_blank" rel="noreferrer">Harness engineering: leveraging Codex in an agent-first world</a>. OpenAI, 2026-02-11.</li><li>Anthropic. <a href="https://www.a

- Ryan Lopopolo. [Harness engineering: leveraging Codex in an agent-first world](https://openai.com/index/harness-engineering/). OpenAI, 2026-02-11.

- Anthropic. [Harness design for long-running application development](https://www.anthropic.com/engineering/harness-design-long-running-apps). 2026-03-24.

- OpenAI. [How evals drive the next chapter in AI for businesses](https://openai.com/index/evals-drive-next-chapter-of-ai/). 2025-11-19.

- Shopify Engineering. [We replaced Redis with MySQL for inventory reservations—and it scaled](https://shopify.engineering/scaling-inventory-reservations). 2026-05-12.

<div class="table-wrap"><table><thead><tr><th>术语</th><th>课程中的含义</th><th>容易混淆的地方</th></tr></thead><tbody><tr><td>Harness Engineering（驭缰工程）</td><td>围绕智能体设计意图、环境、工具、边界、状态和反馈，让工作可以执行、检查、恢复与改进</td><td>不是某个厂商的产品名，也不等于完全无人开发</td></tr><tr><td>model

| eval（评测） | 用任务、环境、样本和证据衡量模型与 harness 的共同表现 | 不等同于单元测试，也不能只看最终答案 |

],   "forbiddenMermaidTypes": ["mindmap"],   "allowedExternalUrlPrefixes": ["https://cdn.jsdelivr.net/npm/mermaid@10/"],

"forbiddenMermaidTypes": ["mindmap"],   "allowedExternalUrlPrefixes": ["https://cdn.jsdelivr.net/npm/mermaid@10/"],   "unregisteredExternalUrlSeverity": "warning"

"allowedExternalUrlPrefixes": ["https://cdn.jsdelivr.net/npm/mermaid@10/"],

Executable file

Executable file

Executable file

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="把 AI 放进代码审查之前，先分清它该接管哪些重复劳动，哪些判断仍必须由人负责。"><title>为什么今天需要 AI Code Review | 如

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="把 AI 放进代码审查之前，先分清它该接管哪些重复劳动，哪些判断仍必须由人负责。"><title>为什么今天需要 AI Code Review | 如何实现高质量的 AI Code 

<p>如果你面对一个新问题，可以依次问五个问题：<strong>它能否被确定性规则表达？需要哪些仓库或业务上下文？报告错误的成本是什么？谁有权接受风险？结果如何验证和回流？</strong> 能够回答这五问，就不会把&quot;采用 AI&quot;误写成&quot;增加一次模型调用&quot;。</p> <h2 id="参考文献">参考文献</h2> <ol><li>Alberto Bacchelli, Christian Bird. <a href="https://do

<ol><li>Alberto Bacchelli, Christian Bird. <a href="https://doi.org/10.1109/ICSE.2013.6606617" target="_blank" rel="noreferrer">Expectations, outcomes, and challenges of modern code review</a>. ICSE, 2013.</li><li>Google Engineering Practic

1. Alberto Bacchelli, Christian Bird. [Expectations, outcomes, and challenges of modern code review](https://doi.org/10.1109/ICSE.2013.6606617). ICSE, 2013.

2. Google Engineering Practices. [The Standard of Code Review](https://google.github.io/eng-practices/review/reviewer/standard.html)；[What to look for in a code review](https://google.github.io/eng-practices/review/reviewer/looking-for.html

3. Shane McIntosh 等. [The impact of code review coverage and code review participation on software quality](https://doi.org/10.1145/2597073.2597076). MSR, 2014.

4. Zhiyu Li 等. [Automating Code Review Activities by Large-Scale Pre-training](https://arxiv.org/abs/2203.09095). ESEC/FSE, 2022.

5. GitHub Docs. [About GitHub Copilot code review](https://docs.github.com/en/copilot/concepts/agents/code-review).

6. Tao Sun 等. [BitsAI-CR: Automated Code Review via LLM in Practice](https://arxiv.org/abs/2501.15134). 2025.

7. Imen Jaoua 等. [Combining Large Language Models with Static Analyzers for Code Review Generation](https://arxiv.org/abs/2502.06633). MSR, 2025.

8. Shweta Ramesh 等. [Automated Code Review Using Large Language Models at Ericsson: An Experience Report](https://arxiv.org/abs/2507.19115). ICSME, 2025.

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="沿一次真实审查请求拆开入口、状态机、批次、MCP、Agent 与结果验证的职责。"><title>从 Prompt 到 Harness：整体架构与核心

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="沿一次真实审查请求拆开入口、状态机、批次、MCP、Agent 与结果验证的职责。"><title>从 Prompt 到 Harness：整体架构与核心思路 | 如何实现高质量的 AI

<p>这一判断也符合公开工程建议：先使用能满足任务的最简单方案，只在性能与可靠性需要时增加 agentic 复杂度。[1] 简单不是少写代码，而是让每个组件都有清楚失败模式。一个 300 行万能 Prompt 往往比五个窄接口更难验证。</p> <h2 id="参考文献">参考文献</h2> <ol><li>Anthropic. <a href="https://www.anthropic.com/engineering/building-effective-agents" 

<ol><li>Anthropic. <a href="https://www.anthropic.com/engineering/building-effective-agents" target="_blank" rel="noreferrer">Building effective agents</a>. 2024-12-19.</li><li>Model Context Protocol. <a href="https://modelcontextprotocol.i

## 参考文献 1. Anthropic. [Building effective agents](https://www.anthropic.com/engineering/building-effective-agents). 2024-12-19.

1. Anthropic. [Building effective agents](https://www.anthropic.com/engineering/building-effective-agents). 2024-12-19.

2. Model Context Protocol. [Architecture, Specification 2025-06-18](https://modelcontextprotocol.io/specification/2025-06-18/architecture). 3. GitHub Docs. [About GitHub Copilot code review](https://docs.github.com/en/copilot/concepts/agent

3. GitHub Docs. [About GitHub Copilot code review](https://docs.github.com/en/copilot/concepts/agents/code-review)；[Using GitHub Copilot code review](https://docs.github.com/en/copilot/how-tos/use-copilot-agents/request-a-code-review/use-co

4. GitLab Docs. [GitLab Duo in merge requests](https://docs.gitlab.com/user/project/merge_requests/duo_in_merge_requests/).

5. Nelson F. Liu 等. [Lost in the Middle: How Language Models Use Long Contexts](https://arxiv.org/abs/2307.03172). TACL, 2023.

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="从 TP、FP、FN 到真实状态枚举，建立一套可复算、能解释排除项的 AICR 指标口径。"><title>先建立度量：采纳率、召回率与 F1-Sco

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="从 TP、FP、FN 到真实状态枚举，建立一套可复算、能解释排除项的 AICR 指标口径。"><title>先建立度量：采纳率、召回率与 F1-Score | 如何实现高质量的 AI

<p>如果你只记住了本章的一个原则，记住这条：<strong>指标的数字不取决于公式，取决于口径。</strong> 口径决定了你看到什么，也决定了你看不见什么。选择什么进入分子、什么进入分母、什么被排除——这些选择塑造了你优化什么、忽略什么。第 4 章开始，你会反复验证每一个工程动作是否真的改变了这些数字，还是仅仅改变了定义这些数字的口径。</p> <h2 id="参考文献">参考文献</h2> <ol><li>scikit-learn. <a href="https://

<ol><li>scikit-learn. <a href="https://scikit-learn.org/stable/modules/model_evaluation.html#precision-recall-and-f-measures" target="_blank" rel="noreferrer">Model evaluation: precision, recall and F-measures</a>.</li><li>Hong Yi Lin 等. <a

## 参考文献 1. scikit-learn. [Model evaluation: precision, recall and F-measures](https://scikit-learn.org/stable/modules/model_evaluation.html#precision-recall-and-f-measures).

1. scikit-learn. [Model evaluation: precision, recall and F-measures](https://scikit-learn.org/stable/modules/model_evaluation.html#precision-recall-and-f-measures).

2. Hong Yi Lin 等. [CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models](https://arxiv.org/abs/2503.16167). Findings of ACL, 2025.

3. Tao Sun 等. [BitsAI-CR: Automated Code Review via LLM in Practice](https://arxiv.org/abs/2501.15134). 2025.

4. Zhiyu Li 等. [Automating Code Review Activities by Large-Scale Pre-training](https://arxiv.org/abs/2203.09095). ESEC/FSE, 2022.

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="低采纳率通常不是一个模型问题，而是一组可以沿规则、上下文、建议和反馈证据逐层定位的系统问题。"><title>采纳率低：问题为什么看起来对，却没人采用

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="低采纳率通常不是一个模型问题，而是一组可以沿规则、上下文、建议和反馈证据逐层定位的系统问题。"><title>采纳率低：问题为什么看起来对，却没人采用 | 如何实现高质量的 AI C

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="提升采纳率要把规则、证据、过滤和反馈做成分层流水线，并用召回率与成本防止系统为了少报而变得沉默。"><title>提升采纳率：规则、上下文、复核与负向

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="提升采纳率要把规则、证据、过滤和反馈做成分层流水线，并用召回率与成本防止系统为了少报而变得沉默。"><title>提升采纳率：规则、上下文、复核与负向记忆 | 如何实现高质量的 AI

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="把&quot;AI 偷懒&quot;还原为可观察的**输出衰减**、**步骤遗漏**和**流程控制失效**，然后从实验证据中找出真正需要解决的问题。"

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="把&quot;AI 偷懒&quot;还原为可观察的**输出衰减**、**步骤遗漏**和**流程控制失效**，然后从实验证据中找出真正需要解决的问题。"><title>召回率低：大型任

<ul><li><code>utils/config.ts</code>：<code>batchAllocation.idealMinLines</code>（800）和 <code>idealMaxLines</code>（1200）定义了批次大小边界；<code>verification</code> 中的 <code>minTimeCoefficient=0</code>、<code>minDensityCoefficient=0</code>、<code>highRi

<h2 id="参考文献">参考文献</h2> <ol><li>Nelson F. Liu 等. <a href="https://arxiv.org/abs/2307.03172" target="_blank" rel="noreferrer">Lost in the Middle: How Language Models Use Long Contexts</a>. TACL, 2023.</li><li>Anthropic. <a href="https://www.

<ol><li>Nelson F. Liu 等. <a href="https://arxiv.org/abs/2307.03172" target="_blank" rel="noreferrer">Lost in the Middle: How Language Models Use Long Contexts</a>. TACL, 2023.</li><li>Anthropic. <a href="https://www.anthropic.com/engineerin

1. Nelson F. Liu 等. [Lost in the Middle: How Language Models Use Long Contexts](https://arxiv.org/abs/2307.03172). TACL, 2023.

2. Anthropic. [Building effective agents](https://www.anthropic.com/engineering/building-effective-agents). 2024-12-19.

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="**用外部**完成证明**、**质量门**和**漏报回流**推动每一批审查真正结束**，让漏掉的问题有路径回到系统中。"><title>提升召回率：分

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="**用外部**完成证明**、**质量门**和**漏报回流**推动每一批审查真正结束**，让漏掉的问题有路径回到系统中。"><title>提升召回率：分批、状态机、质检与数据回流 | 

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="为什么本地跑通了还需要远端服务，以及怎样把审查能力从个人工具变成可被任何系统调用的基础设施。"><title>远端 AI Code Review 云服

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="为什么本地跑通了还需要远端服务，以及怎样把审查能力从个人工具变成可被任何系统调用的基础设施。"><title>远端 AI Code Review 云服务 | 如何实现高质量的 AI 

<p>第 9 章回到原点，把这些技术组件重组成一条可迁移的落地路线。</p> <h2 id="参考文献">参考文献</h2> <p>本章以教学化的 AI Code Review 远端服务案例为主要来源。Git Worktree 的隔离语义参考 <a href="https://git-scm.com/docs/git-worktree" target="_blank" rel="noreferrer">Git 官方文档</a>。监控体系和并发策略为教学化案例设计。</p><n

<p>本章以教学化的 AI Code Review 远端服务案例为主要来源。Git Worktree 的隔离语义参考 <a href="https://git-scm.com/docs/git-worktree" target="_blank" rel="noreferrer">Git 官方文档</a>。监控体系和并发策略为教学化案例设计。</p><nav class="lesson-nav"><a href="../lessons/07-improve-recall-loo

本章以教学化的 AI Code Review 远端服务案例为主要来源。Git Worktree 的隔离语义参考 [Git 官方文档](https://git-scm.com/docs/git-worktree)。监控体系和并发策略为教学化案例设计。

<!doctype html> <html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="九个章节的核心机制重组为一条可迁移的落地路线，以及从今天开始可以做的第一件事。"><title>总结：从单次审查到可持续质量系统 | 如何实现高质量的

<html lang="zh-CN"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><meta name="description" content="九个章节的核心机制重组为一条可迁移的落地路线，以及从今天开始可以做的第一件事。"><title>总结：从单次审查到可持续质量系统 | 如何实现高质量的 AI Code Review<

<p>你的仓库不需要复刻这套系统的全部组件。但你的仓库值得有一套自己的度量、一条自己的反馈通路、一个自己的质量门。**<strong>从今天开始，从记录第一条 Issue 的采纳状态开始</strong>。**</p> <h2 id="参考文献">参考文献</h2> <ol><li>Alberto Bacchelli, Christian Bird. <a href="https://doi.org/10.1109/ICSE.2013.6606617" target="_bl

<h2 id="参考文献">参考文献</h2> <ol><li>Alberto Bacchelli, Christian Bird. <a href="https://doi.org/10.1109/ICSE.2013.6606617" target="_blank" rel="noreferrer">Expectations, outcomes, and challenges of modern code review</a>. ICSE, 2013.</li><li>Go

<ol><li>Alberto Bacchelli, Christian Bird. <a href="https://doi.org/10.1109/ICSE.2013.6606617" target="_blank" rel="noreferrer">Expectations, outcomes, and challenges of modern code review</a>. ICSE, 2013.</li><li>Google Engineering Practic

1. Alberto Bacchelli, Christian Bird. [Expectations, outcomes, and challenges of modern code review](https://doi.org/10.1109/ICSE.2013.6606617). ICSE, 2013.

2. Google Engineering Practices. [The Standard of Code Review](https://google.github.io/eng-practices/review/reviewer/standard.html).

3. Zhiyu Li 等. [Automating Code Review Activities by Large-Scale Pre-training](https://arxiv.org/abs/2203.09095). ESEC/FSE, 2022.

4. Tao Sun 等. [BitsAI-CR: Automated Code Review via LLM in Practice](https://arxiv.org/abs/2501.15134). 2025.

5. Hong Yi Lin 等. [CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models](https://arxiv.org/abs/2503.16167). Findings of ACL, 2025.

6. Imen Jaoua 等. [Combining Large Language Models with Static Analyzers for Code Review Generation](https://arxiv.org/abs/2502.06633). MSR, 2025.

7. Shweta Ramesh 等. [Automated Code Review Using Large Language Models at Ericsson: An Experience Report](https://arxiv.org/abs/2507.19115). ICSME, 2025. 8. GitHub Docs. [About GitHub Copilot code review](https://docs.github.com/en/copilot/

8. GitHub Docs. [About GitHub Copilot code review](https://docs.github.com/en/copilot/concepts/agents/code-review). 9. GitLab Docs. [GitLab Duo in merge requests](https://docs.gitlab.com/user/project/merge_requests/duo_in_merge_requests/). 

9. GitLab Docs. [GitLab Duo in merge requests](https://docs.gitlab.com/user/project/merge_requests/duo_in_merge_requests/).

10. Anthropic. [Building effective agents](https://www.anthropic.com/engineering/building-effective-agents). 2024-12-19.

11. MCP Architecture. [Specification 2025-06-18](https://modelcontextprotocol.io/specification/2025-06-18/architecture).

12. scikit-learn. [Model evaluation](https://scikit-learn.org/stable/modules/model_evaluation.html).

13. Nelson F. Liu 等. [Lost in the Middle: How Language Models Use Long Contexts](https://arxiv.org/abs/2307.03172). TACL, 2023.

14. Git. [git-worktree](https://git-scm.com/docs/git-worktree).

`teach-yourself-skill` 把中文学生可见内容的自然表达作为质量闸门，因此依赖 [op7418/Humanizer-zh](https://github.com/op7418/Humanizer-zh) 提供的可调用 `humanizer-zh` Skill。它不是 Node 或 npm 依赖，也不会被 `SKILL.md` 的 frontmatter 自动安装。

开源发布时，请在仓库 README 的依赖段落链接到 [op7418/Humanizer-zh](https://github.com/op7418/Humanizer-zh)，并按需要记录使用的版本或提交哈希。

#!/usr/bin/env node

Executable file

write(root, "workspace/" + file, "# " + file + "\n");   }   write(root, "workspace/RESOURCES.md", "# Resources\n\n- https://example.com/docs\n");

}   write(root, "workspace/RESOURCES.md", "# Resources\n\n- https://example.com/docs\n");   write(

write(root, "workspace/RESOURCES.md", "# Resources\n\n- https://example.com/docs\n");

root,     "lessons/0001.html",     '<!doctype html><html lang="zh-CN"><head><title>第一章</title></head><body><h1 id="intro">开始</h1><a href="https://example.com/docs">资料</a></body></html>',

"lessons/0001.html",     '<!doctype html><html lang="zh-CN"><head><title>第一章</title></head><body><h1 id="intro">开始</h1><a href="https://example.com/docs">资料</a></body></html>',   );

'<!doctype html><html lang="zh-CN"><head><title>第一章</title></head><body><h1 id="intro">开始</h1><a href="https://example.com/docs">资料</a></body></html>',

href: "lessons/0001.html",           markdown: "markdown/course.md",           sources: [{ url: "https://example.com/docs" }],

markdown: "markdown/course.md",           sources: [{ url: "https://example.com/docs" }],         },

sources: [{ url: "https://example.com/docs" }],