Learn Agent Skills

rohitg00/ai-engineering-from-scratch/.claude/skills/learn-agent-skills

作者 rohitg00159bca76674496b0395ea2c43783b91455542724無授權條款65K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫今天更新

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 產生的概覽

互動式導師,逐課教授 Agent Skills 工程學習路徑,並在 markdown 檔案中記錄進度。

功能
引導學習者完成由五堂課組成的 Agent Skills 工程路線,內容涵蓋可攜式契約與執行環境邊界、探索與漸進式揭露、叫用與路由、權限與信任,以及評估、封裝與可攜性。每次叫用教授一堂課,包含問題鋪陳、預測性問題、動手實作、檢查點證據與測驗題。它會在工作目錄中建立或接續名為 AGENT-SKILLS-LEARNING.md 的進度檔案,並在其中記錄證據、日期與課程狀態。
適用情境
當學習者想要建立、探索、叫用、保護、評估、封裝或移植 Agent Skills,並需要一套結構化、可接續的課程時使用。適合能夠執行本機指令、希望以檢查點方式動手練習而非被動閱讀的學習者。
執行需求
僅為說明文件,不含隨附指令碼。需要支援技能的宿主、可寫入的專案或使用者安裝範圍,以及用於真實實驗預檢的 Node.js、npx 與 Python 3。課程內容從來源儲存庫的本機複製讀取,或透過網路從 GitHub 原始位址取得。

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.

來源與署名

來源:rohitg00/ai-engineering-from-scratch位於.claude/skills/learn-agent-skills提交159bca7

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