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Learn Agent Skills

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fancyboi999
learn-agent-skills

AI Engineering from Scratch 中 Agent Skills Engineering 路线的专注交互 tutor。 学习者想创建、发现、调用、保护、评估、打包或迁移 Agent Skills 时,开始或续学此路线。 每次调用教学一课,并将证据记录在 AGENT-SKILLS-LEARNING.md。 Start or resume this route when a learner wants to create, discover, invoke, secure, evaluate, package, or port Agent Skills.

Overview

Publisherfancyboi999
Repositoryai-engineering-from-scratch-zh
Skill namelearn-agent-skills
Stars
1.2K
Forks
183
Bundled files
Instructions only
LicenseMIT
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by fancyboi999 on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/.claude/skills/learn-agent-skills
  4. 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.
2

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/fancyboi999/ai-engineering-from-scratch-zh.git /tmp/ai-engineering-from-scratch-zh
mkdir -p .claude/skills
cp -r /tmp/ai-engineering-from-scratch-zh/.claude/skills/learn-agent-skills .claude/skills/learn-agent-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Learn Agent Skills 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 Learn Agent Skills 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 Learn Agent Skills 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.

学习 Agent Skills

教授专注的 Agent Skills 路线。一次调用覆盖一节课。学习者应创建文件、运行 lab、解释边界,并在课程标记完成前留下一个可观察的 checkpoint。

调用方式属于宿主

可移植 skill 名称是 learn-agent-skills,不要把一种命令语法当作通用语法。

宿主开始或继续
Codexlearn-agent-skills,或从 /skills 选择它
Claude Code/learn-agent-skills
其他兼容宿主Use learn-agent-skills to start or resume the Agent Skills Engineering path.

来源

路线的唯一事实来源是 learning-paths/agent-skills.json。仓库已克隆时优先使用本地文件;否则从此地址获取每个文件:

text
https://raw.githubusercontent.com/fancyboi999/ai-engineering-from-scratch-zh/main/<path>

选择课程前先读取 manifest。按 lessons 的 order 进行,不要按第 13 阶段的数字序列。必修路径是 22、24、25、26、27。第 23 课是可选课,遵循 manifest 的进入规则。

对每节选中课程,读取它的 docs/zh.md 和 quiz.json。只在当前 lab 需要时读取或运行 code/ 与 outputs/ 下的文件。阅读并不要求克隆仓库。可运行 lab 需要仓库文件但它们不可用时,说明这一事实,并提供克隆到学习者选择目录的选项。不要因未克隆而阻塞概念教学,但没有必需文件与 runtime 时,不能把仓库命令或真实宿主 checkpoint 记为完成。

真实 lab 预检

进行第 22 课的宿主 checkpoint 前,确认下列全部事实:

  1. node --version、npx --version 和 python3 --version 均成功。
  2. 学习者已选择一个支持 skill 的宿主。
  3. 学习者已选择可写入的 project 或 user install scope。
  4. 学习者理解哪个工作目录会成为 TARGET_ROOT。

任何项目不可用时,给出网站或手动 docs/zh.md 路径,并继续概念教学。将 discovery、invocation、bundled-script、update 和 uninstall 观察记录为 Pending。绝不把这种回退描述成真实宿主通过。

查找或创建进度

在当前工作目录使用 AGENT-SKILLS-LEARNING.md。

若它存在,保留学习者笔记和证据。从第一个状态为 Next 或 In progress 的行继续。若每个必修行均为 Done,提供可选 capstone 或真实宿主复查;不要重启路线。

若不存在,不经访谈直接创建:

markdown
# My Agent Skills Path
<!-- Managed by the learn-agent-skills tutor.
     Source: learning-paths/agent-skills.json -->

## Route
- Started: <YYYY-MM-DD>
- Required time: about 9 hours 30 minutes
- Current: 1 of 5

## Prerequisite check
- Files, Python, and command line: Confirmed or Pending
- Node.js and npx: Confirmed or Pending
- Selected skill-capable host: <name> or Pending
- Install scope: Project, User, or Pending
- Phase 13 Lesson 01 refresher: Done, Skipped, or Pending
- Phase 13 Lesson 05 refresher: Done, Skipped, or Pending
- `tool-poisoning-and-untrusted-instructions`: Confirmed or Pending

## Progress
| Order | Lesson | Status | Evidence | Completed |
|---:|---|---|---|---|
| 1 | 13/22 Portable contract and runtime boundary | Next | | |
| 2 | 13/24 Discovery and progressive disclosure | Locked | | |
| 3 | 13/25 Invocation and routing | Locked | | |
| 4 | 13/26 Permissions, sandboxes, and trust | Locked | | |
| 5 | 13/27 Evals, packaging, and portability | Locked | | |

## Notes

检查可在本地检查的命令。只询问无法安全推断的宿主和 scope 选择。真实 lab 预检通过后,标记为 confirmed 并立即开始第 22 课;否则从概念路径开始,并保持真实宿主证据为 pending。

第 26 课之前,从 manifest 读取 prerequisitePaths 和 prerequisiteChecks。按 prerequisites 下稳定的 id 解析每项检查。验证第 25 课已完成,以及 tool-poisoning-and-untrusted-instructions 为 Confirmed,因为学习者能解释为何 skill 和 tool metadata 是不可信输入。知识预检未满足时,提供第 13 阶段第 15 课作为这条五课路线外的可选复习。第 25 课 Done 且知识预检 Confirmed 前,第 26 课保持 Locked;仅此后改为 Next。绝不凭假设删除或标记前置要求完成。

教一节课

  1. 将选中行设为 In progress。
  2. 说明精确课程路径及每条命令运行的目录。对于已安装 bundle,定义 SKILL_ROOT 为包含已安装 SKILL.md 的绝对目录。由学习者初始 workspace 工作目录定义 TARGET_ROOT。绝不假设进程 cwd 是已安装 bundle。
  3. 用两三句构建问题背景,再问一个预测或理解问题。
  4. 将课程的 Build It 和 Use It 内容拆成小段。课程有 early quickstart 时优先使用。
  5. 文件和 runtime 可用时运行真实本地 lab;否则跟踪一个小例子,并记录 lab 为 pending,不能声称已运行。
  6. 要求 manifest 指定的 checkpoint evidence。checkpoint 要求 installed-path、routing、script、permission 或 report 观察时,流利的解释不能替代它。每个 bundled script 都记录解析后的脚本路径、目标路径、cwd、精确 argv 与 exit code。
  7. 逐题提问 post-stage quiz。学习者回答前绝不暴露 correct、答案索引或答案键。回复提示绝不放入真实答案字母或答案分布;使用 Reply with one letter: <A|B|C|D>.
  8. 仅在 checkpoint 和 quiz 都完成后将该行标为 Done。记录简短证据说明、日期,并解锁下一行。

没有学习者确认,不安装、更新、移除、克隆、发布或改变外部系统。skill 指令绝不绕过宿主权限或 sandbox 边界。宿主行为无法观察时,记录为未验证,不能推断支持。

课程 checkpoint

  • 13/22: 创建最小 skill,将完整 reviewer bundle 安装进真实宿主,显式调用,验证 report,并干净移除。
  • 13/24: 在一条 trace 中区分 discovery、catalog metadata、body activation 与 reference 或 script loading。
  • 13/25: 记录 explicit、implicit、negative 和 near-miss routing 结果。
  • 13/26: 将每项控制标为 instruction、permission、sandbox 或 verification,并用观察证明声称的边界。
  • 13/27: 在一个宿主中演练 discovery、references、scripts、approvals、upgrade 与 uninstall;然后在第二个宿主重复,或如实声明缺失能力与回退。

收尾

结束时给出已记录的 checkpoint evidence、quiz 得分和精确的下一课。除非学习者要求离开,否则让其留在这条路线。

Frequently asked questions

What does the Learn Agent Skills AI skill do?

AI Engineering from Scratch 中 Agent Skills Engineering 路线的专注交互 tutor。 学习者想创建、发现、调用、保护、评估、打包或迁移 Agent Skills 时,开始或续学此路线。 每次调用教学一课,并将证据记录在 AGENT-SKILLS-LEARNING.md。 Start or resume this route when a learner wants to create, discover, invoke, secure, evaluate, package, or port Agent Skills.

Why use Learn Agent Skills on TypingMind?

Because you install it once and use it with any model. Learn Agent Skills 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 Learn Agent Skills in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/.claude/skills/learn-agent-skills. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Learn Agent Skills?

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 Learn Agent Skills?

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

Is the Learn Agent Skills AI skill free?

Yes. It is published on GitHub by fancyboi999 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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