본문으로 건너뛰기
cccskills
무료GitHub에 공개

learning-a-tool

Create learning paths for programming tools, and define what information should be researched to create learning guides. Use when user asks to learn, understand, or get started with any programming tool, library, or framework.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(2)

  • SKILL.md2.5 KB
  • references/progressive-learning.md1.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Learning a Tool

Create comprehensive learning paths for programming tools.

Workflow

Phase 1: Research

Gather information from three sources. Research each source independently, then aggregate findings.

From Official Documentation

  • Official docs URL and current version
  • The motivation behind the tool
  • What problem does it solve / what does it help with
  • What types of applications can be built using the tool
  • Use cases
  • Installation steps and prerequisites
  • Core concepts (3-5 fundamental ideas)
  • Official code examples
  • Getting started or tutorial content
  • API reference highlights
  • Known limitations or caveats

From the Repository

  • Repository URL and metadata (stars, last commit, license)
  • Core system architecture (configuration, data processing flow, ...)
  • README quick start section
  • Examples folder contents (what each example demonstrates)
  • Concise summary of the project's main function and the technologies used

From Community Content

  • Top tutorials (title, author, URL, why it's valuable)
  • Video resources (title, channel, duration)
  • Comparison articles (vs alternatives, key tradeoffs)
  • Common gotchas and mistakes people mention
  • Community channels (Discord, Reddit, forums)
  • Real-world use cases and testimonials

Phase 2: Structure

Organize content into progressive levels. references/progressive-learning.md is the source of truth.

You MUST create exactly 5 levels in this order:

  1. Level 1: Overview & Motivation
  2. Level 2: Installation & Hello World
  3. Level 3: Core Concepts
  4. Level 4: Practical Patterns
  5. Level 5: Next Steps

Do NOT merge, skip, or rename levels. Each level's content requirements are defined in the reference file.

Phase 3: Output

Generate the learning path folder.

Output Format

Create the folder in the current working directory (./learning-{tool-name}/) containing:

learning-{tool-name}/
├── README.md           # Overview and how to use this learning path
├── resources.md        # All links organized by source (official, community)
├── learning-path.md    # Main content following the five levels
└── code-examples/      # Runnable code for each section
    ├── 01-hello-world/
    ├── 02-core-concepts/
    └── 03-patterns/

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Provides Typer templates, handles registration, and ensures consistency. ALWAYS use this skill when adding or modifying CLI commands. Use when user requests to add/create/implement/build/write a new command (e.g., "add edit command", "create search feature") OR update/modify/change/edit an existing command.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

Comprehensive diagnostic analysis of time series data. Use when users provide CSV time series data and want to understand its characteristics before forecasting - stationarity, seasonality, trend, forecastability, and transform recommendations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

CraftedWell brand guidelines for presentations and documents. Use this skill whenever creating or styling documents (docx, pdf) or presentations (pptx) for CraftedWell. Apply warm, artisanal aesthetic with chocolate/caramel color palette, Georgia headings, and Arial body text.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

Generate pytest tests for Typer CLI commands. Includes fixtures (temp_storage, sample_data), CliRunner patterns, confirmation handling (y/n/--force), and edge case coverage. Use when user asks to "write tests for", "test my CLI", "add test coverage", or any CLI + test request.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

https-deeplearning-ai/sc-agent-skills-files1.4천2026년 6월 9일 업데이트

https-deeplearning-ai의 스킬 모두 보기

이 스킬의 문제 신고