agentic-learning

agentic-learning is a skill for Claude Code, Codex from hongsw/plugin-for-claude-research. It costs 70 tokens per session (1,597 once invoked), scanned A, original, MIT.

An interactive Korean-language learning framework for teaching Claude Code through a project that automatically creates PowerPoint files.

In plain words
What is it for?
It guides lessons on Claude Code features, with separate work on slide themes, content, and HTML-to-PowerPoint rendering.
Why use it?
It gives learners a staged way to study concepts, practise them, and check their understanding without losing the project context.

Skill for Claude CodeCodex

Part of the domain-research plugin — 2 skills, 1 command, 2 MCP servers shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/hongsw/plugin-for-claude-research/agentic-learning
Any agent
npx skills add hongsw/plugin-for-claude-research --skill agentic-learning
Clone the repo
git clone --depth 1 https://github.com/hongsw/plugin-for-claude-research

Made for: Claude Code, Codex.

Or install domain-research, the plugin that ships this one along with the rest of its 2 skills, 1 command, 2 MCP servers.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agentic-learning

README.md
[![agentmods](https://agentmods.dev/badge/skills/hongsw/plugin-for-claude-research/agentic-learning.svg)](https://agentmods.dev/skills/hongsw/plugin-for-claude-research/agentic-learning)
Your own site
<a href="https://agentmods.dev/skills/hongsw/plugin-for-claude-research/agentic-learning"><img src="https://agentmods.dev/badge/skills/hongsw/plugin-for-claude-research/agentic-learning.svg" alt="Measured on agentmods" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,597 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.01597
Opus 5 $0.00035 $0.00798
Sonnet 5 $0.00014 $0.00319
Haiku 4.5 $0.00007 $0.00160

Measured 5d ago against content hash 303b86c92c18, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

agentic-learning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/domain-research/skills/agentic-learning/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Self-Learning Skill — Claude Code 자기주도 학습

Core Purpose

사용자가 Claude Code의 핵심 기능을 스스로 학습할 수 있도록 돕는 인터랙티브 학습 프레임워크입니다. ai-native-camp/camp-1 커리큘럼을 기반으로 설계되었습니다.

통일 주제: PPTX 자동 생성 프로젝트

모든 레볼루션은 하나의 프로젝트를 공통 예시로 사용합니다.

목표: Claude Code로 PPTX를 자동으로 만드는 팀 시스템 구축

담당 역할 3가지:
  🎨 테마 설정 담당  — 슬라이드 디자인, 색상, 폰트 결정
  ✍️  내용 수정 담당  — 슬라이드 텍스트, 구조, 논리 흐름
  🖨️  렌더링 담당    — HTML → PPTX 변환, 파일 출력

각 레볼루션마다 이 프로젝트에 새로운 Claude Code 기능을 적용하며 점진적으로 완성합니다.


학습 방식: STOP 프로토콜

각 레볼루션은 반드시 2턴 구조를 따릅니다:

Phase A (1턴): 개념 설명 → 실습 지시 → STOP (퀴즈 없음, 질문 없음)

  • 참조 문서의 EXPLAIN 섹션을 읽고 설명
  • 참조 문서의 EXECUTE 섹션을 읽고 실습 안내 (PPTX 프로젝트 맥락 포함)
  • 마무리: "👆 위 내용을 직접 실행해보세요. 실행이 끝나면 '완료' 또는 '다음'이라고 입력해주세요."

Phase B (2턴): 퀴즈 → 피드백 → 다음 레볼루션 안내

  • 참조 문서의 QUIZ 섹션을 읽고 AskUserQuestion으로 퀴즈 출제
  • 정답/오답 피드백 제공
  • 다음 레볼루션으로 이동 여부 확인

절대 규칙

  1. Phase A에서 절대 AskUserQuestion을 호출하지 않는다
  2. Phase A에서 퀴즈 내용을 절대 노출하지 않는다
  3. "해보셨나요?" 같은 질문을 하지 않는다
  4. 각 레볼루션 시작 전 공식 문서 URL을 출력한다
  5. 개념 설명 후 반드시 PPTX 프로젝트에서의 활용 예시를 보여준다

학습 과정 (Learning Pipeline)

레볼루션 0: 환경 설정

Prompt: prompts/setup.md Purpose: Claude Code 설치 및 초기 설정 PPTX 연결: PPTX 프로젝트 디렉토리 구조 만들기 Reference: references/rev0-setup.md

레볼루션 1: 체험 — 먼저 느껴보기

Prompt: prompts/experience.md Purpose: Claude Code의 가능성을 3가지 데모로 체험 PPTX 연결: "PPTX 만들어줘" 한 마디로 슬라이드 생성 체험 Reference: references/rev1-experience.md

레볼루션 2: 왜 터미널인가?

Prompt: prompts/why-cli.md Purpose: CLI 기반 Claude Code의 필요성 이해 PPTX 연결: PPTX 반복 생성 자동화 vs 수작업 비교 Reference: references/rev2-why.md

레볼루션 3: 7대 핵심 기능

Prompt: prompts/core-features.md Purpose: Claude Code 7대 핵심 기능 학습 PPTX 연결: 각 기능을 PPTX 프로젝트에 직접 적용 References:

  • references/rev3-1-claude-md.md — CLAUDE.md → PPTX 스타일 가이드 정의
  • references/rev3-2-skill.md — Skill → pptx-theme-setter 스킬 제작
  • references/rev3-3-mcp.md — MCP → Playwright로 PPTX 렌더링
  • references/rev3-4-subagent.md — Subagent → 테마/내용/렌더링 독립 작업
  • references/rev3-5-agent-teams.md — Agent Teams → 3담당 협업 시스템
  • references/rev3-6-hook.md — Hook → 저장 시 자동 품질 검사
  • references/rev3-7-plugin.md — Plugin → PPTX 도구 패키지 배포

Read the full file on GitHub · 139 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 139 lines · 70 tokens per session scan A 303b86c92c18

Subscribe to this mod's changes

agentic-learning is a skill published in the GitHub repository hongsw/plugin-for-claude-research (20 stars, last pushed 4mo ago), licensed MIT. It adds 70 tokens to every session and 1,597 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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