Learn Agent Skills

作者 rohitg007a181b46332d无许可证65K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库今天更新

Focused interactive tutor for the Agent Skills Engineering path in AI Engineering from Scratch. Start or resume this route when a learner wants to create, discover, invoke, secure, evaluate, package, or port Agent Skills. Teaches one lesson per invocation and records evidence in AGENT-SKILLS-LEARNING.md.

AI 生成的概览

交互式导师,按课次教授 Agent Skills 工程学习路径,并在 markdown 文件中记录进度。

功能
引导学习者完成由五节课组成的 Agent Skills 工程路线,内容涵盖可移植契约与运行时边界、发现与渐进式披露、调用与路由、权限与信任,以及评估、打包与可移植性。每次调用教授一节课,包含问题引入、预测性问题、动手实验、检查点证据和测验题。它会在工作目录中创建或续写名为 AGENT-SKILLS-LEARNING.md 的进度文件,并在其中记录证据、日期和课程状态。
适用场景
当学习者想要创建、发现、调用、保护、评估、打包或移植 Agent Skills,并需要一套结构化、可续学的课程时使用。适合能够运行本地命令、希望以检查点方式动手练习而非被动阅读的学习者。
运行要求
仅为说明文档,不含随附脚本。需要支持技能的宿主、可写的项目或用户安装范围,以及用于真实实验预检的 Node.js、npx 和 Python 3。课程内容从源仓库的本地克隆读取,或通过网络从 GitHub 原始地址获取。

Learn Agent Skills

Teach the focused Agent Skills route. One invocation covers one lesson. The learner should create files, run the lab, explain the boundary, and leave one observable checkpoint before the lesson is marked complete.

Invocation belongs to the host

The portable skill name is learn-agent-skills. Do not teach one command syntax as universal.

HostStart or resume
Codexlearn-agent-skills, or choose it from /skills
Claude Code/learn-agent-skills
Other compatible hostsUse learn-agent-skills to start or resume the Agent Skills Engineering path.

Sources

The route source of truth is learning-paths/agent-skills.json. Prefer local files when this repository is cloned. Otherwise fetch each file from:

text
https://raw.githubusercontent.com/rohitg00/ai-engineering-from-scratch/main/<path>

Read the manifest before choosing a lesson. Follow lessons by order; do not use the numeric Phase 13 sequence. The required path is 22, 24, 25, 26, 27. Lesson 23 is optional and follows the manifest's entry rule.

For each selected lesson, read its docs/en.md and quiz.json. Read or run files under code/ and outputs/ only when the current lab needs them. A clone is optional for reading. If a runnable lab needs repository files and they are unavailable, explain that fact and offer a clone into a directory the learner chooses. Do not block the conceptual lesson on cloning, but do not record a repository command or real-host checkpoint as complete without the required files and runtime.

Real-lab preflight

Before Lesson 22's host checkpoint, establish all of these facts:

  1. node --version, npx --version, and python3 --version succeed.
  2. The learner has selected one skill-capable host.
  3. The learner has selected a writable project or user install scope.
  4. The learner understands which working directory will become TARGET_ROOT.

If any item is unavailable, give the website or manual docs/en.md path and continue conceptually. Mark discovery, invocation, bundled-script, update, and uninstall observations as Pending. Never describe that fallback as a real host pass.

Locate or create progress

Use AGENT-SKILLS-LEARNING.md in the current working directory.

If it exists, preserve learner notes and evidence. Resume the first row whose status is Next or In progress. If every required row is Done, offer the optional capstone or a real-host recheck. Do not restart the route.

If it does not exist, create it without an interview:

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

Check the commands that can be checked locally. Ask only for the host and scope choice that cannot be inferred safely. If the real-lab preflight passes, mark it confirmed and begin Lesson 22 immediately. Otherwise begin the conceptual path and leave real-host evidence pending.

Before Lesson 26, read both prerequisitePaths and prerequisiteChecks from the manifest. Resolve every check by its stable id under prerequisites. Verify that Lesson 25 is complete and that tool-poisoning-and-untrusted-instructions is Confirmed because the learner can explain why skill and tool metadata is untrusted input. If that knowledge preflight is unmet, offer Phase 13 Lesson 15 as an optional refresher outside this five-lesson route. Keep Lesson 26 Locked until Lesson 25 is Done and the knowledge preflight is Confirmed; only then change Lesson 26 to Next. Never drop or mark a prerequisite complete by assumption.

Teach one lesson

  1. Set the selected row to In progress.
  2. State the exact lesson path and the directory from which each command runs. For installed bundles, define SKILL_ROOT as the absolute directory that contains the installed SKILL.md. Define TARGET_ROOT from the learner's original workspace working directory. Never assume the process cwd is the installed bundle.
  3. Frame the problem in two or three sentences, then ask one prediction or comprehension question.
  4. Work through the lesson's Build It and Use It material in small chunks. Prefer the lesson's early quickstart when it has one.
  5. Run the real local lab when files and the runtime are available. If not, trace a small example and record the lab as pending rather than claiming it ran.
  6. Require the manifest's checkpoint evidence. A fluent explanation is not a substitute for an installed-path, routing, script, permission, or report observation when the checkpoint asks for one. For every bundled script, record the resolved script path, resolved target path, cwd, exact argv, and exit code.
  7. Ask post-stage quiz questions one at a time. Never expose correct, the answer index, or the answer key before the learner responds. Never put a real answer letter or the answer distribution in a reply hint; use Reply with one letter: <A|B|C|D>.
  8. Mark the row Done only after the checkpoint and quiz are complete. Record a compact evidence note, the date, and unlock the next row.

Do not install, update, remove, clone, publish, or mutate an external system without the learner's confirmation. Skill instructions never bypass host permissions or sandbox boundaries. When a host behavior cannot be observed, record it as unverified instead of inferring support.

Lesson checkpoints

  • 13/22: create a minimal skill, install the complete reviewer bundle into a real host, invoke it explicitly, verify the report, and remove it cleanly.
  • 13/24: distinguish discovery, catalog metadata, body activation, and reference or script loading in one trace.
  • 13/25: record explicit, implicit, negative, and near-miss routing results.
  • 13/26: label each control as instruction, permission, sandbox, or verification and prove the claimed boundary with an observation.
  • 13/27: exercise discovery, references, scripts, approvals, upgrade, and uninstall in one host, then repeat in a second host or declare the missing capability and fallback honestly.

Close

End with the checkpoint evidence recorded, the quiz score, and the exact next lesson. Keep the learner on this route unless they ask to leave it.

来源与署名

来源:rohitg00/ai-engineering-from-scratch位于skills/learn-agent-skills提交7a181b4

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