explain — for Claude Code explain, varun.surf, community, for Claude Code, ide skills, kiteboarding, kitesurfing, weather-forecast, wind-forecast, **For component interactions:**

v1.0.0

이 스킬 정보

적합한 상황: Ideal for AI agents that need when the user asks to explain something (a feature, data flow, or component), follow this process:. 현지화된 요약: explain helps AI agents handle repository-specific developer workflows with documented implementation details. It covers kiteboarding, kitesurfing, weather-forecast workflows.

기능

When the user asks to explain something (a feature, data flow, or component), follow this process:
Identify What to Explain
Parse the user's request to determine:
Data flow: How data moves from source to destination (e.g., "explain how forecasts get to the
Feature: How a specific feature works end-to-end (e.g., "explain favorites system")

# 핵심 주제

pwittchen pwittchen
[4]
[0]
업데이트: 4/27/2026

Skill Overview

Start with fit, limitations, and setup before diving into the repository.

적합한 상황: Ideal for AI agents that need when the user asks to explain something (a feature, data flow, or component), follow this process:. 현지화된 요약: explain helps AI agents handle repository-specific developer workflows with documented implementation details. It covers kiteboarding, kitesurfing, weather-forecast workflows.

이 스킬을 사용하는 이유

추천 설명: explain helps agents when the user asks to explain something (a feature, data flow, or component), follow this process:. explain helps AI agents handle repository-specific developer workflows with documented

최적의 용도

적합한 상황: Ideal for AI agents that need when the user asks to explain something (a feature, data flow, or component), follow this process:.

실행 가능한 사용 사례 for explain

사용 사례: When the user asks to explain something (a feature, data flow, or component), follow this process:
사용 사례: Identify What to Explain
사용 사례: Parse the user's request to determine:

! 보안 및 제한 사항

  • 제한 사항: Requires repository-specific context from the skill documentation
  • 제한 사항: Works best when the underlying tools and dependencies are already configured

About The Source

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Labs 데모

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ 및 설치 단계

These questions and steps mirror the structured data on this page for better search understanding.

? 자주 묻는 질문

explain은 무엇인가요?

적합한 상황: Ideal for AI agents that need when the user asks to explain something (a feature, data flow, or component), follow this process:. 현지화된 요약: explain helps AI agents handle repository-specific developer workflows with documented implementation details. It covers kiteboarding, kitesurfing, weather-forecast workflows.

explain은 어떻게 설치하나요?

다음 명령을 실행하세요: npx killer-skills add pwittchen/varun.surf. Cursor, Windsurf, VS Code, Claude Code와 19개 이상의 다른 IDE에서 동작합니다.

explain은 어디에 쓰이나요?

주요 활용 사례는 다음과 같습니다: 사용 사례: When the user asks to explain something (a feature, data flow, or component), follow this process:, 사용 사례: Identify What to Explain, 사용 사례: Parse the user's request to determine:.

explain 와 호환되는 IDE는 무엇인가요?

이 스킬은 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer 와 호환됩니다. 통합 설치에는 Killer-Skills CLI를 사용하세요.

explain에 제한 사항이 있나요?

제한 사항: Requires repository-specific context from the skill documentation. 제한 사항: Works best when the underlying tools and dependencies are already configured.

이 스킬 설치 방법

  1. 1. 터미널 열기

    프로젝트 디렉터리에서 터미널 또는 명령줄을 여세요.

  2. 2. 설치 명령 실행

    npx killer-skills add pwittchen/varun.surf 를 실행하세요. CLI가 IDE 또는 에이전트를 자동으로 감지하고 스킬을 설정합니다.

  3. 3. 스킬 사용 시작

    스킬이 이제 활성화되었습니다. 현재 프로젝트에서 explain을 바로 사용할 수 있습니다.

! Source Notes

This page is still useful for installation and source reference. Before using it, compare the fit, limitations, and upstream repository notes above.

Upstream Repository Material

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

explain

Install explain, an AI agent skill for AI agent workflows and automation. Explore features, use cases, limitations, and setup guidance.

SKILL.md
Readonly
Upstream Repository Material
The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

Explain Skill

Explain how data flows through the system, how features work, and trace code paths with clear visualizations and step-by-step breakdowns.

Instructions

When the user asks to explain something (a feature, data flow, or component), follow this process:

1. Identify What to Explain

Parse the user's request to determine:

  • Data flow: How data moves from source to destination (e.g., "explain how forecasts get to the frontend")
  • Feature: How a specific feature works end-to-end (e.g., "explain favorites system")
  • Component: How a specific service or class works internally (e.g., "explain AggregatorService")
  • Integration: How external APIs are integrated (e.g., "explain Windguru integration")

2. Gather Context

Use the following tools to understand the code:

  • Glob to find relevant files
  • Grep to search for specific patterns, method calls, and references
  • Read to examine source code
  • LSP for finding definitions, references, and call hierarchies

3. Trace the Flow

For data flows and features, trace the complete path:

Entry Point → Processing Steps → Output

Identify:

  • Entry points (API endpoints, scheduled tasks, user actions)
  • Service layer processing
  • Data transformations
  • External API calls
  • Caching layers
  • Response formatting

4. Create Visual Diagrams

Use ASCII diagrams to visualize:

For data flows:

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Source    │────▶│  Transform  │────▶│ Destination │
└─────────────┘     └─────────────┘     └─────────────┘

For component interactions:

            ┌──────────────────┐
            │   Controller     │
            └────────┬─────────┘
                     │
        ┌────────────┼────────────┐
        ▼            ▼            ▼
   ┌─────────┐  ┌─────────┐  ┌─────────┐
   │Service A│  │Service B│  │Service C│
   └─────────┘  └─────────┘  └─────────┘

For state transitions:

[State A] ──(action)──▶ [State B] ──(action)──▶ [State C]

5. Provide Step-by-Step Breakdown

Structure the explanation as:

  1. Overview: High-level summary (2-3 sentences)
  2. Entry Point: Where the flow begins
  3. Step-by-Step Flow: Each processing step with file:line references
  4. Key Code Snippets: Important code sections (keep concise)
  5. Data Transformations: How data shape changes
  6. External Dependencies: APIs, databases, caches involved
  7. Error Handling: How errors are managed
  8. Related Components: Other parts of the system that interact

6. Include Code References

Always include file paths with line numbers for easy navigation:

  • src/main/java/.../SpotsController.java:45 - endpoint definition
  • src/main/java/.../AggregatorService.java:120 - data aggregation

Output Format

markdown
1# Explaining: [Topic] 2 3## Overview 4[2-3 sentence summary] 5 6## Visual Diagram 7[ASCII diagram showing the flow] 8 9## Step-by-Step Flow 10 11### 1. [Step Name] 12**File**: `path/to/file.java:line` 13 14[Description of what happens] 15 16```java 17// Key code snippet (if helpful)

2. [Next Step]

...

Data Transformations

StageData ShapeExample
InputType{...}
OutputType{...}

Key Files Involved

  • path/to/file1.java - [purpose]
  • path/to/file2.java - [purpose]
  • [Feature 1]: [brief relation]
  • [Feature 2]: [brief relation]

## Example Topics

Common explanations users might request:

### Data Flows
- "How do forecasts get from Windguru to the frontend?"
- "How are live conditions fetched and displayed?"
- "How does the caching system work?"
- "How does the spot data flow from JSON to API response?"

### Features
- "How does the favorites system work?"
- "How does country filtering work?"
- "How does the search functionality work?"
- "How does theme switching work?"
- "How does the kite size calculator work?"

### Components
- "How does AggregatorService orchestrate data fetching?"
- "How do the FetchCurrentConditionsStrategy implementations work?"
- "How does the ForecastService parse Windguru data?"
- "How does the frontend manage state?"

### Integrations
- "How is Windguru integrated?"
- "How is Google Maps integration working?"
- "How does the AI analysis feature work?"

## Notes

- Keep explanations concise but complete
- Use diagrams to make complex flows understandable
- Always include file:line references for code navigation
- Focus on the specific topic, don't over-explain tangential concerns
- If the topic is ambiguous, ask clarifying questions
- Reference CLAUDE.md, docs/BACKEND.md, and docs/FRONTEND.md for architectural context

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