learn-agent-skills
rohitg00/ai-engineering-from-scratch
Interactive tutor for learning to create, invoke, and secure Agent Skills in AI engineering.
What is learn-agent-skills?
A focused learning path that teaches Agent Skills engineering through hands-on lessons and checkpoints. Use this when you want to master skill creation, discovery, invocation, security, evaluation, packaging, and portability across different AI agent hosts.
- Guides learners through a 5-lesson required path (lessons 22, 24, 25, 26, 27) covering portable contracts, discovery, routing, permissions, and packaging
- Tracks progress in AGENT-SKILLS-LEARNING.md with status, evidence, and completion dates
- Teaches one lesson per invocation with real-lab preflight checks for Node.js, Python, and host setup
- Requires checkpoint evidence (installed paths, routing traces, permission labels, multi-host portability) before marking lessons complete
- Delivers quiz questions one at a time without exposing answers, and unlocks subsequent lessons only when prerequisites are met
- Handles both conceptual and hands-on paths, marking real-host observations as Pending when runtime files are unavailable
How to install learn-agent-skills
npx skills add https://github.com/rohitg00/ai-engineering-from-scratch --skill learn-agent-skills- Node.js (node --version) and npx installed and working
- Python 3 (python3 --version) installed and working
- A skill-capable host selected (Claude Code, Cursor, Codex, or compatible)
- A writable project or user install scope for skill installation
- Familiarity with Phase 13 Lessons 01 and 05 (optional refreshers available)
- Understanding of tool poisoning and untrusted instructions (required before Lesson 26)
How to use learn-agent-skills
- 1.Start or resume the path by invoking learn-agent-skills in your host (e.g., /learn-agent-skills in Claude Code, or learn-agent-skills in Codex)
- 2.Confirm the real-lab preflight: Node.js, Python, host choice, and install scope; the tutor will mark items Confirmed or Pending
- 3.Work through one lesson per invocation, creating files and running labs in your TARGET_ROOT directory
- 4.Provide checkpoint evidence as requested (installed paths, routing traces, permission labels, script execution records)
- 5.Answer quiz questions one at a time; the tutor unlocks the next lesson only after the current one is complete
- 6.Resume from AGENT-SKILLS-LEARNING.md on subsequent invocations; the tutor preserves your notes and progress
Use cases
- Learning to package and distribute reusable skills across Claude Code, Cursor, and other compatible AI agent hosts
- Understanding the boundary between skill metadata (untrusted input) and runtime execution (sandboxed)
- Building a minimal skill, installing it into a real host, invoking it, and verifying behavior before moving to advanced topics
- Mastering permission models, sandbox controls, and verification strategies for secure skill composition
- Practicing multi-host portability by exercising discovery, references, scripts, approvals, and uninstall workflows
- AI engineers learning to build and distribute agent skills
- Developers integrating skills into Claude Code, Cursor, or compatible hosts
- Teams establishing skill security and evaluation practices
- Anyone building reusable, portable AI agent tooling
learn-agent-skills FAQ
The tutor will mark the real-lab preflight as Pending and offer the conceptual path instead. You can still learn the concepts; real-host observations (installed paths, script execution) will remain Pending until you set up the runtime.
No. The tutor enforces the required 5-lesson sequence (22, 24, 25, 26, 27) in order. Lesson 23 is optional and follows the manifest's entry rule. If all required lessons are Done, the tutor offers an optional capstone or a real-host recheck.
Confirmed means the tutor verified the fact locally (e.g., node --version succeeded). Pending means the fact could not be verified and real-host observations are deferred; conceptual learning continues.
Lesson 26 teaches permissions and trust. Before unlocking it, the tutor verifies that you completed Lesson 25 and confirmed understanding of tool poisoning and untrusted instructions—a prerequisite for secure skill composition.
The tutor specifies what evidence each lesson requires (e.g., installed path, routing trace, permission labels, script exit code). Provide the exact observation; a fluent explanation alone is not a substitute for concrete evidence.
Full instructions (SKILL.md)
Source of truth, from rohitg00/ai-engineering-from-scratch.
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:
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:
node --version,npx --version, andpython3 --versionsucceed.- The learner has selected one skill-capable host.
- The learner has selected a writable project or user install scope.
- 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
- Set the selected row to
In progress. - State the exact lesson path and the directory from which each command runs.
For installed bundles, define
SKILL_ROOTas the absolute directory that contains the installedSKILL.md. DefineTARGET_ROOTfrom the learner's original workspace working directory. Never assume the process cwd is the installed bundle. - Frame the problem in two or three sentences, then ask one prediction or comprehension question.
- Work through the lesson's Build It and Use It material in small chunks. Prefer the lesson's early quickstart when it has one.
- 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.
- 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.
- 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; useReply with one letter: <A|B|C|D>. - Mark the row
Doneonly 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.
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