explain

pwittchen's avatarfrom pwittchen

Explain data flows, features, and code paths in the varun.surf application with visual diagrams and step-by-step breakdowns

⭐1stars🔀0forks📁View on GitHub🕐Updated Dec 23, 2025

When & Why to Use This Skill

This Claude skill provides automated code analysis and architectural visualization, enabling developers to understand complex data flows, feature implementations, and code paths through ASCII diagrams and structured step-by-step breakdowns. It streamlines the process of mapping system interactions and tracing data transformations across the entire application stack.

Use Cases

  • Developer Onboarding: Quickly explain how specific features, such as the favorites system or search functionality, are implemented end-to-end with precise file and line references.
  • Data Flow Mapping: Trace the journey of data from external API integrations (like Windguru or Google Maps) through service layers and transformations to the final frontend display.
  • Impact Analysis & Refactoring: Visualize component interactions and state transitions to understand the potential impact of architectural changes or to identify bottlenecks in the code path.
  • Technical Documentation: Automatically generate structured summaries and ASCII flowcharts for complex logic, making it easier to maintain internal knowledge bases and system overviews.
nameexplain
descriptionExplain data flows, features, and code paths in the varun.surf application with visual diagrams and step-by-step breakdowns

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

# Explaining: [Topic]

## Overview
[2-3 sentence summary]

## Visual Diagram
[ASCII diagram showing the flow]

## Step-by-Step Flow

### 1. [Step Name]
**File**: `path/to/file.java:line`

[Description of what happens]

```java
// Key code snippet (if helpful)

2. [Next Step]

...

Data Transformations

Stage Data Shape Example
Input Type {...}
Output Type {...}

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, ARCH.md, and FRONTEND.md for architectural context