Skip to content
cccskills
FreePublished on GitHub

learn-agent-skills

Learn to create, discover, invoke, secure, evaluate, package, and port Agent Skills through one interactive lesson at a time. Practical checkpoints and quizzes track demonstrated progress in a local file, so later sessions resume where you stopped.

OriginalShow the original 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.

See how to install

Good for

  • Learn to build and invoke a minimal Agent Skill
  • Understand discovery and automatic routing
  • Check permission, sandbox, and trust boundaries
  • Practice packaging and portability across hosts
  • Resume lessons using recorded progress

Files included (1)

  • SKILL.md7.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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:

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:

# 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.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

blueprint-figure

FreeSummary

Create static SVG diagrams, scalable images for lessons, READMEs, and manuals. It uses real system names, nine diagram types, and consistent colors and arrows, with checks for readable labels, accessible descriptions, and valid markup.

  • Add a diagram of system interactions to a README
  • Explain state transitions in a manual
  • Illustrate data flow from logs or specifications
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

build-project

FreeSummary

Learn AI engineering by building a project one stage at a time. The tutor guides predictions, learner-written code, automated checks, and reflection, then records progress so the next session can continue from the right stage.

  • Learn AI engineering through hands-on projects
  • Resume a project from the next unfinished stage
  • Find coding mistakes with step-by-step hints
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

check-tests

FreeSummary

Run a local check of test evidence and retain source paths in the result. The workflow stops when required evidence is missing, keeping the findings tied to their sources.

  • Checking local test evidence
  • Keeping source paths in check results
  • Stopping a check when evidence is missing
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

Test your understanding of a phase in AI Engineering from Scratch through eight multiple-choice questions. Receive a score, explanations for incorrect answers, and specific lessons to review before continuing your studies.

  • Checking your understanding after completing a phase
  • Assessing readiness for the next phase
  • Finding lessons to review from incorrect answers
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

Prepare for four Claude certification tracks through guided lessons, practical exercises, quizzes, and mock exams. The tutor checks understanding and learner-created work, records progress, and uses assessment results to guide review.

  • Choosing a certification track for a learning goal
  • Resuming lessons from saved progress
  • Completing guided exercises without writing code
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

course-guide

FreeSummary

Find relevant lessons in AI Engineering from Scratch from a topic, question, or bug. Get a short selection of lessons, necessary prerequisites, and the next learning command, with dedicated routes for specialized subjects.

  • Finding lessons on a topic you want to learn
  • Locating lessons that explain a bug's underlying cause
  • Choosing what to study next based on your progress
rohitg00/ai-engineering-from-scratch71.1KUpdated Oct 18, 2026

See all skills by rohitg00

Report a problem with this skill