learn-agent-skills — скилл для Claude Code: разбор и установка
Пошаговый интерактивный тьютор по разработке скиллов для ИИ-агентов. Проводит через практические уроки, проверяет окружение и фиксирует прогресс в локальном файле.
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a claude-codeЧто делает learn-agent-skills
Скилл запускает интерактивный курс по созданию, вызову, изоляции и тестированию инструментов агента. За одно обращение ассистент разбирает ровно один урок из манифеста learning-paths/agent-skills.json. Программа содержит пять обязательных тем: от описания контракта среды до проверки прав доступа и упаковки готовых бандлов.
Для выполнения лабораторных работ требуется локальное окружение с рабочими командами node, npx и python3. Если исполняемые файлы или репозиторий недоступны на машине, тьютор переходит в теоретический режим и оставляет системные чекпоинты со статусом ожидания. Вся история прохождения и заметки пишутся в файл AGENT-SKILLS-LEARNING.md в текущей рабочей директории.
Без прямого подтверждения пользователя скилл не меняет системные настройки, не клонирует репозитории и не ставит пакеты. Урок по безопасности остаётся заблокированным до тех пор, пока ученик не подтвердит понимание рисков отравления контекста инструментами.
Какие задачи решает
- освоить контракт рантайма и изоляцию скиллов для агентов
- пройти практические лабораторные работы по вызову инструментов
- сохранять подтверждённый прогресс обучения в
AGENT-SKILLS-LEARNING.md - проверить готовность
node,npxиpython3перед запуском тестов
Примеры запросов агенту
- Запусти
/learn-agent-skills, чтобы разобрать первый урок по контракту рантайма. - Используй
learn-agent-skills, чтобы проверить прогресс вAGENT-SKILLS-LEARNING.mdи продолжить курс. - Начни практический урок по безопасности скиллов через команду
/learn-agent-skills.
Как установить learn-agent-skills
1Через Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a claude-code2Вручную: положить файлы
~/.claude/skills/learn-agent-skills/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/learn-agent-skills/
1Через Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a codex2Вручную: положить файлы
.agents/skills/learn-agent-skills/SKILL.mdДля всех проектов — ~/.agents/skills/
1Через Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a cursor2Вручную: положить файлы
.cursor/skills/learn-agent-skills/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install rohitg00/ai-engineering-from-scratch learn-agent-skills2Вручную: положить файлы
.github/skills/learn-agent-skills/SKILL.md1Через Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a gemini-cli2Командой платформы
gemini skills install https://github.com/rohitg00/ai-engineering-from-scratch --path skills/learn-agent-skillsВручную: положить файлы
.devin/skills/learn-agent-skills/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Через Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a opencodeClaude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
По шагам, с командами для каждой платформы: Как установить скилл в Claude Code: пять способов
Вопросы о learn-agent-skills
Как установить learn-agent-skills в Claude Code?
Выполните команду npx skills add rohitg00/ai-engineering-from-scratch --skill learn-agent-skills -a claude-code. Манифест скилла будет сохранён по пути ~/.claude/skills/learn-agent-skills/SKILL.md.
Что делает learn-agent-skills?
Скилл пошагово обучает созданию, маршрутизации, изоляции и оценке навыков для ИИ-агентов. За одно обращение он объясняет один урок, задаёт контрольные вопросы и записывает результаты в AGENT-SKILLS-LEARNING.md.
Что нужно подготовить перед запуском практических заданий?
Перед чекпоинтом первого практического урока требуются установленные node, npx и python3. Если эти утилиты недоступны, тьютор предложит разобрать материал в теоретическом формате.
Исходный текст
SKILL.md · MIT
---
name: learn-agent-skills
description: >
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.
---
# 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.
| Host | Start or resume |
|---|---|
| Codex | `learn-agent-skills`, or choose it from `/skills` |
| Claude Code | `/learn-agent-skills` |
| Other compatible hosts | `Use 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.
© rohitg00 · MIT · rohitg00/ai-engineering-from-scratch