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code-deep-analysis

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Mis à jour5 mars 2026 à 07:34

Performs deep analysis of code repositories like DeepWiki. Use it to examine project structure, identify technologies, analyze architecture, detect design patterns, evaluate code quality, and generate exhaustive technical documentation. Supports three operation modes - RAG (contextual analysis), Deep Research (multi-turn investigation), and Simple Chat (direct technical responses). Ideal for understanding unknown codebases, performing technical due diligence, or documenting existing projects.

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FiveTechSoft

FiveTechSoft/deepwiki_skill

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

SKILL.md

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Exécutez n'importe quel Skill en un clic

name	code-deep-analysis
description	Performs deep analysis of code repositories like DeepWiki. Use it to examine project structure, identify technologies, analyze architecture, detect design patterns, evaluate code quality, and generate exhaustive technical documentation. Supports three operation modes - RAG (contextual analysis), Deep Research (multi-turn investigation), and Simple Chat (direct technical responses). Ideal for understanding unknown codebases, performing technical due diligence, or documenting existing projects.
schema_version	1.0
category	code-analysis
version	1.0.0

Deep Code Analysis Skill

This skill allows you to analyze code repositories exhaustively, generating a complete understanding of the project similar to what DeepWiki offers. The analysis includes structure, architecture, technologies, patterns, and code quality.

It operates in three modes: contextual RAG analysis, multi-turn Deep Research, and direct Simple Chat — each with specific behaviors and focus levels suited to different investigation needs.

When to Use This Skill

When you need to understand an unknown codebase
To perform technical due diligence on projects
When documenting existing software architectures
To identify technical debt and improvement opportunities
When evaluating the overall quality of a project
To generate automatic code documentation
For deep, focused investigation of a specific functionality
For technical audit of a specific file or module
For iterative evaluation of an implementation
To generate a consolidated technical conclusion

Inputs

Parameter	Type	Required	Description
`repo_path`	string	yes	Local path or URL of the repository to analyze
`repo_name`	string	yes	Name of the repository
`user_query`	string	yes	Specific question or topic to investigate within the repository
`mode`	string	no	Operation mode: `rag`, `deep_research`, or `simple_chat` (auto-detected if omitted)
`conversation_history`	object	no	Structured history of previous conversation to maintain continuity in multi-turn investigations
`contexts`	list	no	Relevant file fragments retrieved via semantic search
`research_iteration`	integer	no	Current iteration number in Deep Research mode
`language_name`	string	no	Language explicitly requested by the user for the response

Outputs

Parameter	Type	Description
`response`	string	Structured Markdown response with technical analysis, iterative research, or final conclusion depending on the active mode
`html_file`	string	(Optional) Path to the generated HTML file when HTML output is requested. The HTML follows the DeepWiki dark-theme interface layout

Operation Modes

This skill operates in three main modes, each with specific behavior:

Mode	Purpose	Iterations	Focus Level
RAG	Contextual response based on files	1	High
Deep Research	Deep multi-turn investigation	Multiple	Very High
Simple Chat	Direct technical response	1	Specific

Mode 1: RAG (Contextual Analysis)

Role: You are a code assistant that answers user questions on a repository. You receive the user query, relevant context from files, and past conversation history.

Purpose: Answer specific questions using the user's query, context retrieved from files, and conversation history.

Behavior:

Automatically detects the language of the query
Responds in the same language
If a specific language is requested, it takes priority over the query language
Uses structured Markdown
Organizes information with headings and lists
Cites file paths using inline code formatting
For code blocks, use triple backticks with language specification (```harbour, ```c, ```javascript, etc.)
Use ## headings for major sections
Use bullet points or numbered lists where appropriate
Format tables using markdown table syntax when presenting structured data
Use bold and italic for emphasis

Context Processing: The RAG mode processes information in this order:

System prompt (role and formatting rules)
Conversation history (previous Q&A turns, if any)
Retrieved contexts (file fragments with file paths)
Current user prompt

Strict Rules:

Do NOT include ```markdown fences at the beginning or end of the answer
Start the response directly with the content
Think step by step and ensure the answer is well-structured and visually organized
The content will already be rendered as markdown, so just provide the raw markdown content
Maintain clear visual organization

Mode 2: Deep Research (Multi-Turn Investigation)

Designed for deep, strictly focused investigation across multiple iterations.

Role: You are an expert code analyst examining a repository. You are conducting a multi-turn Deep Research process to thoroughly investigate the specific topic in the user's query. Your goal is to provide detailed, focused information EXCLUSIVELY about this topic.

First Iteration

Guidelines:

This is the first iteration of a multi-turn research process focused EXCLUSIVELY on the user's query
Start the response with ## Research Plan
Outline the approach to investigating this specific topic
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature
Clearly state the specific topic being researched to maintain focus throughout all iterations
Identify the key aspects that need to be researched
Provide initial findings based on the information available
End with ## Next Steps indicating what will be investigated in the next iteration
Do NOT provide a final conclusion yet — this is just the beginning of the research
Do NOT include general repository information unless directly relevant to the query
Remember that this topic will be maintained across all research iterations

Restrictions:

Do NOT deviate from the specific topic
Do NOT include irrelevant general information
NEVER respond with just "Continue the research" as an answer — always provide substantive research findings
Do NOT respond with empty messages
Focus EXCLUSIVELY on the specific topic being researched — do not drift to related topics
The research MUST directly address the original question

Style:

Be concise but thorough
Use markdown formatting to improve readability
Cite specific files and code sections when relevant

Intermediate Iterations

Guidelines:

CAREFULLY review the conversation history to understand what has been researched so far
The response MUST build on previous research iterations — do NOT repeat information already covered
Identify gaps or areas that need further exploration related to this specific topic
Focus on one specific aspect that needs deeper investigation in this iteration
Start the response with ## Research Update {iteration_number}
Clearly explain what is being investigated in this iteration
Provide new insights that weren't covered in previous iterations
Maintain continuity with previous research iterations — this is a continuous investigation
Do NOT include general repository information unless directly relevant to the query
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature

If it is the penultimate iteration (e.g., iteration 3 of 4), prepare a synthesis for closure in the next iteration.

Restrictions:

Do NOT deviate from the main focus — focus EXCLUSIVELY on the specific topic
NEVER respond with just "Continue the research" as an answer — always provide substantive research findings
The research MUST directly address the original question

Style:

Be concise but thorough
Focus on providing new information, not repeating what's already been covered
Use markdown formatting to improve readability
Cite specific files and code sections when relevant

Final Iteration

Guidelines:

This is the final iteration of the research process
CAREFULLY review the entire conversation history to understand all previous findings
Synthesize ALL findings from previous iterations into a comprehensive conclusion
Start with ## Final Conclusion
The conclusion MUST directly address the original question
Stay STRICTLY focused on the specific topic — do not drift to related topics
Include specific code references and implementation details related to the topic
Highlight the most important discoveries and insights about this specific functionality
Provide a complete and definitive answer to the original question
Ensure the conclusion builds on and references key findings from previous iterations
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature
May include actionable recommendations or insights when appropriate

Forbidden:

Deviating to related topics
Responding with "Continue the research" as an answer — always provide a complete conclusion
Responding with open or incomplete phrases
Including general repository information unless directly relevant to the query

Style:

Be concise but thorough
Use markdown formatting to improve readability
Cite specific files and code sections when relevant
Structure the response with clear headings
End with actionable insights or recommendations when appropriate

Mode 3: Simple Chat (Direct Response)

Role: You are an expert code analyst providing direct, concise, and accurate information about code repositories. You NEVER start responses with markdown headers or code fences.

Direct technical response mode.

Characteristics:

Answer the user's question directly without ANY preamble or filler phrases
Do NOT include any rationale, explanation, or extra comments before the answer
Do NOT start with preambles like "Okay, here's a breakdown" or "Here's an explanation"
Do NOT start with markdown headers like ## Analysis of... or any file path references
Do NOT start with ```markdown code fences
Do NOT end the response with ``` closing fences
Do NOT start by repeating or acknowledging the question
JUST START with the direct answer to the question
Start with the most relevant information that directly addresses the user's query

Anti-pattern example (DO NOT do this):

## Analysis of `source/classes/xbrowse.prg`

This file contains...

Instead, just start directly with:

TXBrowse is a powerful data grid control that supports...

Style:

Format the response with proper markdown including headings, lists, and code blocks WITHIN the answer (not wrapping it)
For code analysis, organize the response with clear sections
Think step by step and structure the answer logically
Use concise, direct language
Prioritize accuracy over verbosity
When showing code, include line numbers and file paths when relevant
Use markdown formatting to improve readability
Be precise and technical when discussing code
The response language should match the user's query language

How to Run the Analysis

Phase 1: Initial Exploration

Identify the project type
- Detect the main programming language
- Identify the framework(s) used
- Determine the application type (web, mobile, CLI, API, desktop, library, etc.)
Map the directory structure
- List all top-level directories
- Identify organizational patterns (DDD, MVC, Clean Architecture, layered, etc.)
- Locate main configuration files
- Measure directory depth and breadth
Examine configuration files
- package.json, pyproject.toml, Cargo.toml, pom.xml, Makefile, .hbp, etc.
- Build files: webpack.config.js, tsconfig.json, Makefile, .bat/.sh scripts
- Container configuration: Dockerfile, docker-compose.yml
- IDE/editor configuration: .editorconfig, .vscode/, .agent/

Phase 2: Technology Analysis

Main technology stack
- Languages and versions used
- Backend and frontend frameworks
- Databases and caching systems
- Message queues and external services
- AI/ML integrations
Critical dependencies
- Main libraries and their purpose
- Dependencies with known vulnerabilities
- Outdated or unmaintained packages
- Internal vs external dependency ratio
Development tools
- Linters and formatters used
- Testing systems
- CI/CD tools
- Task runners and bundlers
- Build system complexity

Phase 3: Architecture Analysis

Architectural patterns
- Identify whether it uses MVC, MVP, MVVM, Clean Architecture, Hexagonal, etc.
- Detect design patterns used (Factory, Observer, Strategy, Composite, Bridge, etc.)
- Identify specific architectures (microservices, serverless, monolith)
- Map class inheritance hierarchies
- Generate a class hierarchy diagram using [quote][mermaid]...[/mermaid][/quote] syntax
- Generate an architecture layers diagram showing the layered structure
Component structure
- Main modules and their responsibilities
- Dependencies between components
- Application entry and exit points
- Communication patterns between components
- Coupling and cohesion assessment
- Generate a component dependency diagram showing inter-module relationships
Data flow
- How information flows through the system
- APIs and contracts between modules
- Integrations with external services
- Event/callback patterns
- Generate a data flow diagram showing how data moves through the system

Phase 4: Code Analysis

Overall quality
- Readability and maintainability
- Cyclomatic complexity
- Code duplication
- Function and module length
- Naming conventions consistency
Good patterns identified
- SOLID principles applied
- Dependency injection
- Consistent error handling
- Logging and monitoring
- Data validation
- Documentation coverage
Areas for improvement
- Code smells detected
- Frequent anti-patterns
- Lack of documentation in critical functions
- Insufficient testing coverage
- Monolithic files needing refactoring
- Hardcoded values or paths

Phase 5: Testing and Quality

Testing strategy
- Types of tests implemented (unit, integration, e2e)
- Testing frameworks used
- Current code coverage
- Testing patterns employed
- Sample/example coverage as implicit testing
CI/CD
- Continuous integration pipeline
- Deployment stages
- Branching strategies
- Release workflow
- Build automation level

Phase 6: Report Generation

Report structure
- Executive summary
- System architecture (with Mermaid diagrams using [quote][mermaid]...[/mermaid][/quote] syntax)
- Complete technology stack (with Mermaid mindmap or pie chart)
- Component breakdown by category
- Quantitative metrics table
- Code quality analysis with scoring
- Design patterns identified (with Mermaid class diagrams)
- Notable innovations
- Findings and recommendations (prioritized)
- Build pipeline diagram
- Event/callback flow diagrams
Output format
- Structured Markdown
- Clear and navigable sections
- Code examples when relevant
- Actionable recommendations
- ALL Mermaid diagrams MUST use [quote][mermaid]...[/mermaid][/quote] syntax (never use ```mermaid fences)
- Generate as many Mermaid diagrams as possible to visually illustrate the analysis
- Tables for metrics and comparisons
- HTML output: When requested, convert the Markdown to a standalone HTML file using deepwiki-template.html (see HTML Output Generation section below)

Decision Tree

The following decision tree should be used to determine the analysis mode and approach. When generating this in a report, use the Mermaid syntax:

[quote][mermaid] flowchart TD A["User Query"] --> B{"Query Type?"} B -->|"Specific file/function"| C["RAG Mode"] B -->|"Broad investigation"| D["Deep Research Mode"] B -->|"Quick question"| E["Simple Chat Mode"]

D --> F{"Multiple services?"}
F -->|"Yes"| G["Identify inter-service communication"]
F -->|"No"| H["Analyze as monolith"]

D --> I{"Existing documentation?"}
I -->|"Yes"| J["Compare with implementation"]
I -->|"No"| K["Generate from code"]

D --> L{"Has tests?"}
L -->|"Yes"| M["Analyze coverage and quality"]
L -->|"No"| N["Flag as critical improvement area"]

D --> O{"Multi-language?"}
O -->|"Yes"| P["Analyze each layer, then map interactions"]
O -->|"No"| Q["Focus on single-language patterns"]

[/mermaid][/quote]

Output Format — DeepWiki Page Style

The analysis MUST generate output structured as wiki-style pages that resemble the DeepWiki interface. The output is a single markdown document, but it is organized as multiple logical "pages" separated by --- dividers. Each page follows the conventions below.

CRITICAL: All Mermaid diagrams MUST use [quote][mermaid]...[/mermaid][/quote] syntax. NEVER use ```mermaid ``` fences.

Page Structure Conventions

Every logical page/section follows this structure:

Page Title — An # or ## heading acting as the page name
Relevant source files — A blockquote listing the key source files related to this page, each with file path and optional line range (e.g., include/fivewin.ch#8-9). Format: > 📄 path/to/file.ext or > 📄 path/to/file.ext#L10-25
Introduction paragraph — One or two sentences summarizing the page, with cross-references to other sections written as bold links (e.g., "For detailed class internals see Core Architecture. For build scripts see Build and Platform Support.")
Subsections (###) — Each with descriptive prose-style text (not just bullet lists). Write flowing, well-structured paragraphs that explain concepts, followed by code examples, tables, or diagrams as needed
Source citations inline — Reference specific source files with line numbers inline using backtick formatting: `source/classes/window.prg#L45-60`
Code snippets — Show relevant code fragments using fenced code blocks with language tags
Tables — Use markdown tables for structured data (compiler targets, component lists, metrics, etc.)
Mermaid diagrams — Using [quote][mermaid]...[/mermaid][/quote] syntax wherever a visual aid helps understanding

Sidebar Navigation Structure

At the very beginning of the document, include a navigation index representing the wiki's sidebar. Use a nested list mirroring the structure shown below. Adapt the items to the actual project being analyzed:

## 📑 Navigation

- **Overview**
- **Getting Started**
  - Installation
  - Building Applications
  - Hello World Tutorial
  - Sample Applications
- **Core Architecture**
  - Window System (TWindow)
  - Dialog System
  - Control System (TControl)
  - Event Handling
  - Data Binding Pattern
  - MDI Framework
- **Data Access Layer**
  - Data Access Architecture
  - Database Connector Summary
- **UI Controls**
  - TXBrowse — Advanced Data Grid
  - TGet — Input Fields
  - [other major controls]
- **AI and Modern Features**
- **Build and Platform Support**
- **Settings**

Wiki Page Template

Below is the template for each page. Replace bracketed items with actual content:

# [Page Title]

> 📄 Relevant source files
> 
> `[file_path_1]#L[start]-[end]` — [brief description]
> `[file_path_2]` — [brief description]
> `[file_path_3]#L[start]-[end]` — [brief description]

[Introduction paragraph in flowing prose. Cross-reference other pages:
"For installation steps see **Installation**. For detailed class internals see
**Core Architecture**. For build scripts and compiler targets see **Build and Platform Support**."]

## [First Subsection Title]

[Descriptive, flowing prose explaining this aspect of the project. Not just bullet points — write
real paragraphs that read naturally, as a wiki article would.]

[Optional: framework version defined in `include/fivewin.ch#L8-9`:]

    #define FWVERSION    "FWH 25.12"
    #define FW_VersionNo 25120

[Continuation of the explanation, referencing source code inline like
`source/classes/window.prg#L45` when citing specific implementations.]

| Column 1 | Column 2 | Column 3 |
|---|---|---|
| Data | Data | Data |

## [Second Subsection Title]

[More prose-style content explaining the next concept...]

[INSERT MERMAID diagram using [quote][mermaid]...[/mermaid][/quote] syntax]

## [Third Subsection Title]

[Continue with additional subsections as needed...]

Mandatory Pages to Generate

The following pages MUST be generated for any project analysis. Adapt titles and content to match the project:

Page	Content	Key Diagrams
Overview	Project introduction, what it is, version, purpose, subsystem map	Subsystem map (flowchart), tech stack (pie)
Getting Started	Installation, building, hello world, sample apps	Build pipeline (flowchart)
Core Architecture	Main class hierarchy, design patterns, layers	Class hierarchy (classDiagram), layers (graph TD)
Window/UI System	Window classes, control hierarchy, event handling	Class diagram, event sequence diagram
Data Access Layer	Database connectivity, supported backends, ORMs	ER diagram, component dependency
UI Controls	Major controls (grids, inputs, menus, etc.) breakdown	Component relationship diagram
AI and Modern Features	AI integrations, web tech, modern additions	Dependency diagram
Build and Platform Support	Compilers, targets, makefiles, platform matrix	Build pipeline (flowchart)

Style Guidelines for Prose

Write like a wiki article, NOT like a technical report with bullet lists
Use flowing paragraphs that explain concepts naturally
Start each page with a summary paragraph that gives context
Use cross-references to other pages: "For more details see Core Architecture"
Cite source files inline: "The framework version is defined in include/fivewin.ch#L8-9"
Show code snippets indented or in fenced blocks when illustrating specific definitions
Use tables for structured comparisons (compiler matrix, component lists, etc.)
Every page should have a "Relevant source files" blockquote at the top
Keep an academic/encyclopedic tone — informative, neutral, precise

HTML Output Generation

The skill can generate a standalone HTML file that replicates the DeepWiki dark-theme interface. This is the preferred output format when the user requests a visual, browsable wiki.

Files Involved

File	Purpose
`deepwiki-template.html`	Self-contained HTML template with dark theme, 3-column layout (sidebar, content, TOC), Mermaid.js rendering, highlight.js syntax highlighting, search, and responsive design
`md2html.js`	Node.js script that converts the skill's Markdown output into a standalone HTML file using the template

When to Generate HTML

When the user explicitly asks for HTML output
When the user mentions "like DeepWiki" or "visual wiki"
When doing a full repository analysis (the default output should include HTML)
When the user asks to "see" or "browse" the documentation

Method 1: Using the Conversion Script

After generating the Markdown analysis, run:

node md2html.js analysis.md output.html --repo-owner=OwnerName --repo-name=RepoName

The script will:

Extract the ## 📑 Navigation block to build the sidebar
Convert [quote][mermaid]...[/mermaid][/quote] to <div class="mermaid"> for rendering
Split content at --- dividers into separate wiki pages
Generate TOC from h2/h3 headings for the right sidebar
Inject everything into the template and produce a single, self-contained HTML file

Method 2: Direct HTML Generation (Preferred)

The agent can also generate the HTML directly by:

Reading deepwiki-template.html as a reference for the structure and CSS
Replacing the {{PLACEHOLDERS}} with generated content:
- {{REPO_OWNER}} — Repository owner/organization name
- {{REPO_NAME}} — Repository name
- {{NAV_ITEMS}} — HTML for the sidebar navigation tree
- {{PAGE_CONTENT}} — HTML for all wiki pages wrapped in <div class="wiki-page"> elements
- {{TOC_ITEMS}} — HTML for the right-side "On this page" links
Writing the complete HTML file to the output location

Template Placeholder Details

`{{NAV_ITEMS}}` — Sidebar Navigation

Each navigation item uses this structure:

<div class="nav-section">
    <a class="nav-item" data-page="page-overview" onclick="navigateTo('page-overview')">
        <svg class="nav-icon" viewBox="0 0 16 16" fill="currentColor">...</svg>
        Overview
    </a>
</div>

For nested items, increase padding-left in increments of 20px (36px, 56px, etc.).

`{{PAGE_CONTENT}}` — Wiki Pages

Each page is wrapped in a div. The first page should have the active class:

<div class="wiki-page active" id="page-overview">
    <h1>Overview</h1>
    <div class="source-files-box" onclick="toggleSourceFiles(this)">
        <span class="icon">📄</span> Relevant source files
        <span class="chevron">›</span>
    </div>
    <div class="source-files-list">
        <a class="source-file-item" href="#">include/fivewin.ch#L8-9</a>
    </div>
    <p>Page content here...</p>
    <div class="mermaid">
        graph TD
            A["Layer 1"] --> B["Layer 2"]
    </div>
</div>
<div class="wiki-page" id="page-getting-started">
    ...
</div>

`{{TOC_ITEMS}}` — Table of Contents

<a class="toc-link" href="#section-id">Section Title</a>
<a class="toc-link depth-3" href="#subsection-id">Subsection Title</a>

CSS Classes Reference

Class	Usage
`.wiki-page`	Wrapper for each page section, use `.active` to show
`.source-files-box`	Collapsible "Relevant source files" header
`.source-files-list`	Container for source file links
`.source-file-item`	Individual source file link
`.mermaid`	Mermaid diagram container (auto-rendered by Mermaid.js)
`.nav-item`	Sidebar navigation item, use `.active` for current page
`.nav-children`	Collapsible child nav container, use `.open` to expand
`.toc-link`	Right sidebar TOC link, use `.depth-3` for h3 indentation
`.code-block-wrapper`	Auto-generated wrapper for code blocks with copy button

Design Specifications

The template faithfully replicates the DeepWiki interface:

Element	Specification
Background	`#0d1117` (base), `#161b22` (surface), `#1c2129` (overlay)
Text	`#e6edf3` (primary), `#8b949e` (secondary), `#6e7681` (tertiary)
Accent	`#1f6feb` (blue), `#3fb950` (green), `#58a6ff` (links)
Font	Inter (sans), JetBrains Mono (code) — loaded from Google Fonts CDN
Sidebar width	280px (left), 220px (right TOC)
Content max-width	820px
Header height	48px
Mermaid theme	Dark mode with matching color variables
Responsive	TOC hidden at 1200px, sidebar collapses at 768px

Language Handling

The skill:

Detects the language of the user's query automatically
Responds in the SAME language as the user's query
IMPORTANT: If a specific language is requested in the prompt, that language takes priority over the detected query language
Maintains linguistic consistency across ALL iterations in Deep Research mode
Never switches language mid-iteration
Code comments and technical terms may remain in the original language of the codebase

Formatting Rules

All responses must:

Use structured Markdown with proper syntax for all formatting
For code blocks, use triple backticks with language specification (```harbour, ```c, ```javascript, etc.)
Use ## headings for major sections
Use bullet points or numbered lists where appropriate
Format tables using markdown table syntax when presenting structured data
Use bold and italic for emphasis
Reference file paths as inline code
Maintain visual clarity
Include emoji indicators for priority levels (🔴🟡🟢)

Mermaid Diagram Syntax (MANDATORY)

ALL Mermaid diagrams MUST use this custom syntax:

[quote][mermaid]
...mermaid code here (raw, WITHOUT ```mermaid fences)...
[/mermaid][/quote]

Rules:

NEVER use ```mermaid ``` fences for diagrams
ALWAYS wrap Mermaid code inside [quote][mermaid]...[/mermaid][/quote]
The Mermaid code goes directly between the tags, with NO additional code fences
Generate as many Mermaid diagrams as possible to visually illustrate the analysis
Every architecture section, class hierarchy, data flow, build pipeline, event system, and component relationship SHOULD have an accompanying Mermaid diagram

Correct example:

[quote][mermaid]
classDiagram
    class TWindow {
        +hWnd
        +Paint()
        +End()
    }
    TWindow <|-- TDialog
    TWindow <|-- TControl
[/mermaid][/quote]

INCORRECT example (DO NOT do this):

```mermaid
classDiagram
    class TWindow { ... }
```

Critical formatting constraints:

Do NOT include ```markdown fences at the beginning or end of the answer
Start the response directly with the content
The content will already be rendered as markdown, so just provide the raw markdown content
Think step by step and ensure the answer is well-structured and visually organized

Focus Enforcement

The skill guarantees:

Exclusive focus on the queried topic
Continuity in multi-turn investigations
Technical coherence between iterations
Avoidance of topic drift
Responses directly aligned with the original question
If the topic is about a specific file or feature, ONLY that file or feature is analyzed
General repository information is excluded unless directly relevant to the query
NEVER responds with just filler phrases like "Continue the research" — always provides substantive findings
Cross-references previous iteration findings to build a coherent narrative

Mermaid Diagram Guidelines

The analysis MUST generate as many Mermaid diagrams as possible. Below are the mandatory diagram types to include when applicable. All diagrams use [quote][mermaid]...[/mermaid][/quote] syntax.

1. Class Hierarchy Diagram

Use classDiagram to show inheritance and composition between classes:

[quote][mermaid] classDiagram class BaseClass { +dataMembers +Method1() +Method2() } class ChildA { +SpecificData +OverriddenMethod() } class ChildB { +OtherData +AnotherMethod() } BaseClass <|-- ChildA BaseClass <|-- ChildB BaseClass *-- HelperClass [/mermaid][/quote]

2. Architecture Layers Diagram

Use graph TD (top-down) to show layered architectures:

[quote][mermaid] graph TD A["Application Layer"] --> B["Framework / DSL Layer"] B --> C["OOP Classes Layer"] C --> D["Utility Functions"] D --> E["API Wrappers / Bindings"] E --> F["Operating System / Runtime"] [/mermaid][/quote]

3. Data Flow Diagram

Use flowchart LR (left-right) to show how data moves through the system:

[quote][mermaid] flowchart LR A["User Input"] --> B["Validation"] B --> C["Business Logic"] C --> D["Data Access Layer"] D --> E[("Database")] C --> F["Rendering"] F --> G["Screen Output"] [/mermaid][/quote]

4. Build Pipeline Diagram

Use flowchart LR to illustrate the build process and toolchain:

[quote][mermaid] flowchart LR A[".prg Source"] --> B["Harbour Compiler"] B --> C[".c Generated"] C --> D["C/C++ Compiler"] D --> E[".obj Files"] F[".c Source"] --> D G[".cpp Source"] --> D E --> H["Librarian / Linker"] H --> I[".lib / .exe"] [/mermaid][/quote]

5. Component Dependency Diagram

Use graph LR to show dependencies between modules:

[quote][mermaid] graph LR UI["UI Controls"] --> Core["Core Framework"] DB["Database Layer"] --> Core Net["Networking"] --> Core AI["AI Integration"] --> Net AI --> Core Reports["Reporting"] --> UI Reports --> DB Web["WebView"] --> UI Web --> Net [/mermaid][/quote]

6. Event / Callback Flow Diagram

Use sequenceDiagram to show event handling and callback patterns:

[quote][mermaid] sequenceDiagram participant User participant Window participant Control participant EventHandler

User->>Window: Click/KeyPress
Window->>Control: WndProc dispatch
Control->>EventHandler: Evaluate bAction/bWhen
EventHandler-->>Control: Result
Control-->>Window: Refresh/Update
Window-->>User: Visual feedback

[/mermaid][/quote]

7. Design Patterns Diagram

Use classDiagram to illustrate identified design patterns:

[quote][mermaid] classDiagram class Subject { +Attach(observer) +Notify() } class Observer { +Update() } class ConcreteObserver { +Update() } Subject --> Observer : notifies Observer <|-- ConcreteObserver [/mermaid][/quote]

8. Technology Stack Diagram

Use pie or mindmap to show technology distribution:

[quote][mermaid] pie title Code Distribution by Language "Harbour/xBase" : 460 "C" : 200 "C++" : 40 "Headers" : 102 [/mermaid][/quote]

9. State Diagram

Use stateDiagram-v2 to model lifecycle states of key objects:

[quote][mermaid] stateDiagram-v2 [] --> Created : New() Created --> Active : Activate() Active --> Updated : Refresh() Updated --> Active Active --> Destroyed : End() Destroyed --> [] [/mermaid][/quote]

10. ER Diagram (Data Model)

Use erDiagram when the project has database entities:

[quote][mermaid] erDiagram CUSTOMER ||--o{ ORDER : places ORDER ||--|{ LINE_ITEM : contains PRODUCT ||--o{ LINE_ITEM : "ordered in" [/mermaid][/quote]

When to Include Each Diagram

Diagram Type	When to Include
Class Hierarchy	Always (if the project has classes)
Architecture Layers	Always (for any multi-layered project)
Data Flow	When data processing pipelines exist
Build Pipeline	When the build system is non-trivial
Component Dependencies	When there are 3+ distinct modules
Event/Callback Flow	When event-driven patterns are used
Design Patterns	When recognizable patterns are found
Technology Stack	Always (pie chart of code distribution)
State Diagram	When objects have clear lifecycle states
ER Diagram	When database entities are present

Usage Examples

Full analysis of an unknown project

Analyze the repository at /workspace/my-project as DeepWiki would

Focus on a specific aspect

Perform an architecture analysis of the project focusing on design patterns

Comparison with best practices

Evaluate the code quality comparing with clean code principles

Deep research on a specific module

Investigate the database connectivity layer in depth using Deep Research mode

Quick question about a file

What does the TXBrowse class do and what are its main methods?

Metrics to Collect

Number of files per language
Total lines of code
Maximum directory depth
Number of direct dependencies
Test coverage (if applicable)
Average cyclomatic complexity
Average number of functions/classes per file
Largest files by line count
Class inheritance depth
Number of samples/examples

Prompt Template Reference

For integration with embedding/RAG pipelines, the context processing follows this template structure:

<START_OF_SYS_PROMPT>
{system_prompt}
{output_format_str}
<END_OF_SYS_PROMPT>

{# If conversation history exists #}
<START_OF_CONVERSATION_HISTORY>
{for each dialog_turn in conversation_history}
  {turn_number}.
  User: {user_query}
  You: {assistant_response}
{end for}
<END_OF_CONVERSATION_HISTORY>

{# If file contexts are provided #}
<START_OF_CONTEXT>
{for each context in contexts}
  {index}.
  File Path: {context.file_path}
  Content: {context.text}
{end for}
<END_OF_CONTEXT>

<START_OF_USER_PROMPT>
{user_input}
<END_OF_USER_PROMPT>

Deep Research iterations use role/guidelines/style blocks:

<role>
  Expert analyst identity, repository info, language constraint, iteration context
</role>

<guidelines>
  Iteration-specific behavioral rules (first / intermediate / final)
</guidelines>

<style>
  Output formatting preferences (concise, markdown, citations)
</style>

This structure ensures consistent behavior whether the skill is invoked as a standalone agent, integrated with a semantic search engine, or orchestrated through a multi-turn pipeline.

Available Helper Scripts

The skill includes optional Harbour scripts that can be used during the analysis:

analyze-structure.prg: Analyzes the directory structure and generates a tree with file counts and sizes
detect-tech-stack.prg: Detects technologies based on file extensions and configuration files
calculate-metrics.prg: Calculates code metrics (lines per language, file counts, directory depth)

analyze-structure.prg

/*
 * Directory Structure Analyzer
 * Usage: analyze-structure <path> [max_depth]
 * Generates a visual tree of the directory structure
 */

#include "directry.ch"

FUNCTION Main( cPath, cMaxDepth )

   LOCAL nMaxDepth := 3

   DEFAULT cPath     := "."
   DEFAULT cMaxDepth := "3"

   nMaxDepth := Val( cMaxDepth )

   ? "Directory Structure Analysis"
   ? Replicate( "=", 40 )
   ? ""

   AnalyzeDir( cPath, 0, nMaxDepth )

RETURN NIL

STATIC FUNCTION AnalyzeDir( cPath, nLevel, nMaxDepth )

   LOCAL aFiles, aFile
   LOCAL nFiles := 0, nDirs := 0
   LOCAL cIndent := Replicate( "  ", nLevel )

   IF nLevel > nMaxDepth
      RETURN NIL
   ENDIF

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF

      IF "D" $ aFile[ F_ATTR ]
         nDirs++
         ? cIndent + "[DIR] " + aFile[ F_NAME ]
         AnalyzeDir( cPath + "\" + aFile[ F_NAME ], nLevel + 1, nMaxDepth )
      ELSE
         nFiles++
      ENDIF
   NEXT

   ? cIndent + "  (" + LTrim( Str( nFiles ) ) + " files, " + ;
     LTrim( Str( nDirs ) ) + " subdirs)"

RETURN NIL

detect-tech-stack.prg

/*
 * Technology Stack Detector
 * Usage: detect-tech-stack <path>
 * Detects programming languages and frameworks from file extensions
 * and configuration files
 */

FUNCTION Main( cPath )

   LOCAL aExtensions := {}
   LOCAL aTechFiles  := { ;
      { "package.json",     "Node.js / JavaScript" }, ;
      { "pyproject.toml",   "Python"               }, ;
      { "Cargo.toml",       "Rust"                  }, ;
      { "pom.xml",          "Java (Maven)"          }, ;
      { "build.gradle",     "Java (Gradle)"         }, ;
      { "Makefile",         "Make build system"     }, ;
      { "Dockerfile",       "Docker"                }, ;
      { "docker-compose.yml", "Docker Compose"      }, ;
      { ".hbp",             "Harbour"               }, ;
      { "fivewin.ch",       "FiveWin for Harbour"   }, ;
      { "tsconfig.json",    "TypeScript"            }, ;
      { "webpack.config.js","Webpack"               }, ;
      { "go.mod",           "Go"                    }, ;
      { "CMakeLists.txt",   "CMake"                 }, ;
      { ".csproj",          "C# / .NET"             }  ;
   }

   DEFAULT cPath := "."

   ? "Technology Stack Detection"
   ? Replicate( "=", 40 )
   ? ""

   // Detect by config files
   ? "## Detected Technologies"
   DetectByConfigFiles( cPath, aTechFiles )

   ? ""
   ? "## Languages by Extension"
   CountByExtension( cPath, aExtensions )

RETURN NIL

STATIC FUNCTION DetectByConfigFiles( cPath, aTechFiles )

   LOCAL aItem

   FOR EACH aItem IN aTechFiles
      IF File( cPath + "\" + aItem[ 1 ] ) .OR. ;
         File( cPath + "\include\" + aItem[ 1 ] )
         ? "  [✓] " + aItem[ 2 ] + " (" + aItem[ 1 ] + ")"
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountByExtension( cPath, aExtensions )

   LOCAL aLangs := { ;
      { ".prg", "Harbour/xBase", 0 }, ;
      { ".c",   "C",             0 }, ;
      { ".cpp", "C++",           0 }, ;
      { ".h",   "C/C++ Header",  0 }, ;
      { ".ch",  "Clipper Header", 0 }, ;
      { ".js",  "JavaScript",    0 }, ;
      { ".ts",  "TypeScript",    0 }, ;
      { ".py",  "Python",        0 }, ;
      { ".rb",  "Ruby",          0 }, ;
      { ".go",  "Go",            0 }, ;
      { ".rs",  "Rust",          0 }, ;
      { ".java","Java",          0 }, ;
      { ".cs",  "C#",            0 }, ;
      { ".bat", "Batch script",  0 }, ;
      { ".sh",  "Shell script",  0 }, ;
      { ".md",  "Markdown",      0 }, ;
      { ".html","HTML",          0 }, ;
      { ".css", "CSS",           0 }  ;
   }
   LOCAL aItem

   CountFilesRecursive( cPath, aLangs )

   FOR EACH aItem IN aLangs
      IF aItem[ 3 ] > 0
         ? "  " + PadR( aItem[ 2 ], 20 ) + LTrim( Str( aItem[ 3 ] ) ) + " files"
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountFilesRecursive( cPath, aLangs )

   LOCAL aFiles, aFile, aItem, cExt

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF
      IF "D" $ aFile[ F_ATTR ]
         IF aFile[ F_NAME ] != ".git"
            CountFilesRecursive( cPath + "\" + aFile[ F_NAME ], aLangs )
         ENDIF
      ELSE
         cExt := Lower( SubStr( aFile[ F_NAME ], RAt( ".", aFile[ F_NAME ] ) ) )
         FOR EACH aItem IN aLangs
            IF cExt == aItem[ 1 ]
               aItem[ 3 ]++
               EXIT
            ENDIF
         NEXT
      ENDIF
   NEXT

RETURN NIL

calculate-metrics.prg

/*
 * Code Metrics Calculator
 * Usage: calculate-metrics <path>
 * Calculates lines of code, file counts, and complexity estimates
 */

#include "directry.ch"

STATIC nTotalLines  := 0
STATIC nTotalFiles  := 0
STATIC nMaxDepth    := 0
STATIC nLargestFile := 0
STATIC cLargestName := ""

FUNCTION Main( cPath )

   LOCAL aCodeExts := { ".prg", ".c", ".cpp", ".h", ".ch", ".js", ".ts", ;
                        ".py", ".go", ".rs", ".java", ".cs" }

   DEFAULT cPath := "."

   ? "Code Metrics Report"
   ? Replicate( "=", 40 )
   ? ""

   ProcessDir( cPath, aCodeExts, 0 )

   ? ""
   ? "## Summary"
   ? "  Total source files:  " + LTrim( Str( nTotalFiles ) )
   ? "  Total lines of code: " + LTrim( Str( nTotalLines ) )
   ? "  Max directory depth: " + LTrim( Str( nMaxDepth ) )
   ? "  Largest file:        " + cLargestName + ;
     " (" + LTrim( Str( nLargestFile ) ) + " lines)"

   IF nTotalFiles > 0
      ? "  Avg lines per file:  " + LTrim( Str( Int( nTotalLines / nTotalFiles ) ) )
   ENDIF

RETURN NIL

STATIC FUNCTION ProcessDir( cPath, aCodeExts, nDepth )

   LOCAL aFiles, aFile, cExt, nLines

   IF nDepth > nMaxDepth
      nMaxDepth := nDepth
   ENDIF

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF
      IF "D" $ aFile[ F_ATTR ]
         IF aFile[ F_NAME ] != ".git" .AND. aFile[ F_NAME ] != "node_modules"
            ProcessDir( cPath + "\" + aFile[ F_NAME ], aCodeExts, nDepth + 1 )
         ENDIF
      ELSE
         cExt := Lower( SubStr( aFile[ F_NAME ], RAt( ".", aFile[ F_NAME ] ) ) )
         IF AScan( aCodeExts, cExt ) > 0
            nTotalFiles++
            nLines := CountLines( cPath + "\" + aFile[ F_NAME ] )
            nTotalLines += nLines
            IF nLines > nLargestFile
               nLargestFile := nLines
               cLargestName := cPath + "\" + aFile[ F_NAME ]
            ENDIF
         ENDIF
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountLines( cFile )

   LOCAL nHandle, cLine, nCount := 0

   nHandle := FOpen( cFile )

   IF nHandle >= 0
      DO WHILE ! HB_FEof( nHandle )
         cLine := HB_FReadLine( nHandle )
         nCount++
      ENDDO
      FClose( nHandle )
   ENDIF

RETURN nCount

Run any of these scripts with Harbour: hbrun analyze-structure.prg <path>

name	code-deep-analysis
description	Performs deep analysis of code repositories like DeepWiki. Use it to examine project structure, identify technologies, analyze architecture, detect design patterns, evaluate code quality, and generate exhaustive technical documentation. Supports three operation modes - RAG (contextual analysis), Deep Research (multi-turn investigation), and Simple Chat (direct technical responses). Ideal for understanding unknown codebases, performing technical due diligence, or documenting existing projects.
schema_version	1.0
category	code-analysis
version	1.0.0

Deep Code Analysis Skill

It operates in three modes: contextual RAG analysis, multi-turn Deep Research, and direct Simple Chat — each with specific behaviors and focus levels suited to different investigation needs.

When to Use This Skill

When you need to understand an unknown codebase
To perform technical due diligence on projects
When documenting existing software architectures
To identify technical debt and improvement opportunities
When evaluating the overall quality of a project
To generate automatic code documentation
For deep, focused investigation of a specific functionality
For technical audit of a specific file or module
For iterative evaluation of an implementation
To generate a consolidated technical conclusion

Inputs

Parameter	Type	Required	Description
`repo_path`	string	yes	Local path or URL of the repository to analyze
`repo_name`	string	yes	Name of the repository
`user_query`	string	yes	Specific question or topic to investigate within the repository
`mode`	string	no	Operation mode: `rag`, `deep_research`, or `simple_chat` (auto-detected if omitted)
`conversation_history`	object	no	Structured history of previous conversation to maintain continuity in multi-turn investigations
`contexts`	list	no	Relevant file fragments retrieved via semantic search
`research_iteration`	integer	no	Current iteration number in Deep Research mode
`language_name`	string	no	Language explicitly requested by the user for the response

Outputs

Parameter	Type	Description
`response`	string	Structured Markdown response with technical analysis, iterative research, or final conclusion depending on the active mode
`html_file`	string	(Optional) Path to the generated HTML file when HTML output is requested. The HTML follows the DeepWiki dark-theme interface layout

Operation Modes

This skill operates in three main modes, each with specific behavior:

Mode	Purpose	Iterations	Focus Level
RAG	Contextual response based on files	1	High
Deep Research	Deep multi-turn investigation	Multiple	Very High
Simple Chat	Direct technical response	1	Specific

Mode 1: RAG (Contextual Analysis)

Role: You are a code assistant that answers user questions on a repository. You receive the user query, relevant context from files, and past conversation history.

Purpose: Answer specific questions using the user's query, context retrieved from files, and conversation history.

Behavior:

Automatically detects the language of the query
Responds in the same language
If a specific language is requested, it takes priority over the query language
Uses structured Markdown
Organizes information with headings and lists
Cites file paths using inline code formatting
For code blocks, use triple backticks with language specification (```harbour, ```c, ```javascript, etc.)
Use ## headings for major sections
Use bullet points or numbered lists where appropriate
Format tables using markdown table syntax when presenting structured data
Use bold and italic for emphasis

Context Processing: The RAG mode processes information in this order:

System prompt (role and formatting rules)
Conversation history (previous Q&A turns, if any)
Retrieved contexts (file fragments with file paths)
Current user prompt

Strict Rules:

Do NOT include ```markdown fences at the beginning or end of the answer
Start the response directly with the content
Think step by step and ensure the answer is well-structured and visually organized
The content will already be rendered as markdown, so just provide the raw markdown content
Maintain clear visual organization

Mode 2: Deep Research (Multi-Turn Investigation)

Designed for deep, strictly focused investigation across multiple iterations.

First Iteration

Guidelines:

This is the first iteration of a multi-turn research process focused EXCLUSIVELY on the user's query
Start the response with ## Research Plan
Outline the approach to investigating this specific topic
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature
Clearly state the specific topic being researched to maintain focus throughout all iterations
Identify the key aspects that need to be researched
Provide initial findings based on the information available
End with ## Next Steps indicating what will be investigated in the next iteration
Do NOT provide a final conclusion yet — this is just the beginning of the research
Do NOT include general repository information unless directly relevant to the query
Remember that this topic will be maintained across all research iterations

Restrictions:

Do NOT deviate from the specific topic
Do NOT include irrelevant general information
NEVER respond with just "Continue the research" as an answer — always provide substantive research findings
Do NOT respond with empty messages
Focus EXCLUSIVELY on the specific topic being researched — do not drift to related topics
The research MUST directly address the original question

Style:

Be concise but thorough
Use markdown formatting to improve readability
Cite specific files and code sections when relevant

Intermediate Iterations

Guidelines:

CAREFULLY review the conversation history to understand what has been researched so far
The response MUST build on previous research iterations — do NOT repeat information already covered
Identify gaps or areas that need further exploration related to this specific topic
Focus on one specific aspect that needs deeper investigation in this iteration
Start the response with ## Research Update {iteration_number}
Clearly explain what is being investigated in this iteration
Provide new insights that weren't covered in previous iterations
Maintain continuity with previous research iterations — this is a continuous investigation
Do NOT include general repository information unless directly relevant to the query
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature

If it is the penultimate iteration (e.g., iteration 3 of 4), prepare a synthesis for closure in the next iteration.

Restrictions:

Do NOT deviate from the main focus — focus EXCLUSIVELY on the specific topic
NEVER respond with just "Continue the research" as an answer — always provide substantive research findings
The research MUST directly address the original question

Style:

Be concise but thorough
Focus on providing new information, not repeating what's already been covered
Use markdown formatting to improve readability
Cite specific files and code sections when relevant

Final Iteration

Guidelines:

This is the final iteration of the research process
CAREFULLY review the entire conversation history to understand all previous findings
Synthesize ALL findings from previous iterations into a comprehensive conclusion
Start with ## Final Conclusion
The conclusion MUST directly address the original question
Stay STRICTLY focused on the specific topic — do not drift to related topics
Include specific code references and implementation details related to the topic
Highlight the most important discoveries and insights about this specific functionality
Provide a complete and definitive answer to the original question
Ensure the conclusion builds on and references key findings from previous iterations
If the topic is about a specific file or feature (like "Dockerfile"), focus ONLY on that file or feature
May include actionable recommendations or insights when appropriate

Forbidden:

Deviating to related topics
Responding with "Continue the research" as an answer — always provide a complete conclusion
Responding with open or incomplete phrases
Including general repository information unless directly relevant to the query

Style:

Be concise but thorough
Use markdown formatting to improve readability
Cite specific files and code sections when relevant
Structure the response with clear headings
End with actionable insights or recommendations when appropriate

Mode 3: Simple Chat (Direct Response)

Role: You are an expert code analyst providing direct, concise, and accurate information about code repositories. You NEVER start responses with markdown headers or code fences.

Direct technical response mode.

Characteristics:

Answer the user's question directly without ANY preamble or filler phrases
Do NOT include any rationale, explanation, or extra comments before the answer
Do NOT start with preambles like "Okay, here's a breakdown" or "Here's an explanation"
Do NOT start with markdown headers like ## Analysis of... or any file path references
Do NOT start with ```markdown code fences
Do NOT end the response with ``` closing fences
Do NOT start by repeating or acknowledging the question
JUST START with the direct answer to the question
Start with the most relevant information that directly addresses the user's query

Anti-pattern example (DO NOT do this):

## Analysis of `source/classes/xbrowse.prg`

This file contains...

Instead, just start directly with:

TXBrowse is a powerful data grid control that supports...

Style:

Format the response with proper markdown including headings, lists, and code blocks WITHIN the answer (not wrapping it)
For code analysis, organize the response with clear sections
Think step by step and structure the answer logically
Use concise, direct language
Prioritize accuracy over verbosity
When showing code, include line numbers and file paths when relevant
Use markdown formatting to improve readability
Be precise and technical when discussing code
The response language should match the user's query language

How to Run the Analysis

Phase 1: Initial Exploration

Identify the project type
- Detect the main programming language
- Identify the framework(s) used
- Determine the application type (web, mobile, CLI, API, desktop, library, etc.)
Map the directory structure
- List all top-level directories
- Identify organizational patterns (DDD, MVC, Clean Architecture, layered, etc.)
- Locate main configuration files
- Measure directory depth and breadth
Examine configuration files
- package.json, pyproject.toml, Cargo.toml, pom.xml, Makefile, .hbp, etc.
- Build files: webpack.config.js, tsconfig.json, Makefile, .bat/.sh scripts
- Container configuration: Dockerfile, docker-compose.yml
- IDE/editor configuration: .editorconfig, .vscode/, .agent/

Phase 2: Technology Analysis

Main technology stack
- Languages and versions used
- Backend and frontend frameworks
- Databases and caching systems
- Message queues and external services
- AI/ML integrations
Critical dependencies
- Main libraries and their purpose
- Dependencies with known vulnerabilities
- Outdated or unmaintained packages
- Internal vs external dependency ratio
Development tools
- Linters and formatters used
- Testing systems
- CI/CD tools
- Task runners and bundlers
- Build system complexity

Phase 3: Architecture Analysis

Architectural patterns
- Identify whether it uses MVC, MVP, MVVM, Clean Architecture, Hexagonal, etc.
- Detect design patterns used (Factory, Observer, Strategy, Composite, Bridge, etc.)
- Identify specific architectures (microservices, serverless, monolith)
- Map class inheritance hierarchies
- Generate a class hierarchy diagram using [quote][mermaid]...[/mermaid][/quote] syntax
- Generate an architecture layers diagram showing the layered structure
Component structure
- Main modules and their responsibilities
- Dependencies between components
- Application entry and exit points
- Communication patterns between components
- Coupling and cohesion assessment
- Generate a component dependency diagram showing inter-module relationships
Data flow
- How information flows through the system
- APIs and contracts between modules
- Integrations with external services
- Event/callback patterns
- Generate a data flow diagram showing how data moves through the system

Phase 4: Code Analysis

Overall quality
- Readability and maintainability
- Cyclomatic complexity
- Code duplication
- Function and module length
- Naming conventions consistency
Good patterns identified
- SOLID principles applied
- Dependency injection
- Consistent error handling
- Logging and monitoring
- Data validation
- Documentation coverage
Areas for improvement
- Code smells detected
- Frequent anti-patterns
- Lack of documentation in critical functions
- Insufficient testing coverage
- Monolithic files needing refactoring
- Hardcoded values or paths

Phase 5: Testing and Quality

Testing strategy
- Types of tests implemented (unit, integration, e2e)
- Testing frameworks used
- Current code coverage
- Testing patterns employed
- Sample/example coverage as implicit testing
CI/CD
- Continuous integration pipeline
- Deployment stages
- Branching strategies
- Release workflow
- Build automation level

Phase 6: Report Generation

Report structure
- Executive summary
- System architecture (with Mermaid diagrams using [quote][mermaid]...[/mermaid][/quote] syntax)
- Complete technology stack (with Mermaid mindmap or pie chart)
- Component breakdown by category
- Quantitative metrics table
- Code quality analysis with scoring
- Design patterns identified (with Mermaid class diagrams)
- Notable innovations
- Findings and recommendations (prioritized)
- Build pipeline diagram
- Event/callback flow diagrams
Output format
- Structured Markdown
- Clear and navigable sections
- Code examples when relevant
- Actionable recommendations
- ALL Mermaid diagrams MUST use [quote][mermaid]...[/mermaid][/quote] syntax (never use ```mermaid fences)
- Generate as many Mermaid diagrams as possible to visually illustrate the analysis
- Tables for metrics and comparisons
- HTML output: When requested, convert the Markdown to a standalone HTML file using deepwiki-template.html (see HTML Output Generation section below)

Decision Tree

The following decision tree should be used to determine the analysis mode and approach. When generating this in a report, use the Mermaid syntax:

D --> F{"Multiple services?"}
F -->|"Yes"| G["Identify inter-service communication"]
F -->|"No"| H["Analyze as monolith"]

D --> I{"Existing documentation?"}
I -->|"Yes"| J["Compare with implementation"]
I -->|"No"| K["Generate from code"]

D --> L{"Has tests?"}
L -->|"Yes"| M["Analyze coverage and quality"]
L -->|"No"| N["Flag as critical improvement area"]

D --> O{"Multi-language?"}
O -->|"Yes"| P["Analyze each layer, then map interactions"]
O -->|"No"| Q["Focus on single-language patterns"]

[/mermaid][/quote]

Output Format — DeepWiki Page Style

CRITICAL: All Mermaid diagrams MUST use [quote][mermaid]...[/mermaid][/quote] syntax. NEVER use ```mermaid ``` fences.

Page Structure Conventions

Every logical page/section follows this structure:

Page Title — An # or ## heading acting as the page name
Relevant source files — A blockquote listing the key source files related to this page, each with file path and optional line range (e.g., include/fivewin.ch#8-9). Format: > 📄 path/to/file.ext or > 📄 path/to/file.ext#L10-25
Introduction paragraph — One or two sentences summarizing the page, with cross-references to other sections written as bold links (e.g., "For detailed class internals see Core Architecture. For build scripts see Build and Platform Support.")
Subsections (###) — Each with descriptive prose-style text (not just bullet lists). Write flowing, well-structured paragraphs that explain concepts, followed by code examples, tables, or diagrams as needed
Source citations inline — Reference specific source files with line numbers inline using backtick formatting: `source/classes/window.prg#L45-60`
Code snippets — Show relevant code fragments using fenced code blocks with language tags
Tables — Use markdown tables for structured data (compiler targets, component lists, metrics, etc.)
Mermaid diagrams — Using [quote][mermaid]...[/mermaid][/quote] syntax wherever a visual aid helps understanding

Sidebar Navigation Structure

## 📑 Navigation

- **Overview**
- **Getting Started**
  - Installation
  - Building Applications
  - Hello World Tutorial
  - Sample Applications
- **Core Architecture**
  - Window System (TWindow)
  - Dialog System
  - Control System (TControl)
  - Event Handling
  - Data Binding Pattern
  - MDI Framework
- **Data Access Layer**
  - Data Access Architecture
  - Database Connector Summary
- **UI Controls**
  - TXBrowse — Advanced Data Grid
  - TGet — Input Fields
  - [other major controls]
- **AI and Modern Features**
- **Build and Platform Support**
- **Settings**

Wiki Page Template

Below is the template for each page. Replace bracketed items with actual content:

# [Page Title]

> 📄 Relevant source files
> 
> `[file_path_1]#L[start]-[end]` — [brief description]
> `[file_path_2]` — [brief description]
> `[file_path_3]#L[start]-[end]` — [brief description]

[Introduction paragraph in flowing prose. Cross-reference other pages:
"For installation steps see **Installation**. For detailed class internals see
**Core Architecture**. For build scripts and compiler targets see **Build and Platform Support**."]

## [First Subsection Title]

[Descriptive, flowing prose explaining this aspect of the project. Not just bullet points — write
real paragraphs that read naturally, as a wiki article would.]

[Optional: framework version defined in `include/fivewin.ch#L8-9`:]

    #define FWVERSION    "FWH 25.12"
    #define FW_VersionNo 25120

[Continuation of the explanation, referencing source code inline like
`source/classes/window.prg#L45` when citing specific implementations.]

| Column 1 | Column 2 | Column 3 |
|---|---|---|
| Data | Data | Data |

## [Second Subsection Title]

[More prose-style content explaining the next concept...]

[INSERT MERMAID diagram using [quote][mermaid]...[/mermaid][/quote] syntax]

## [Third Subsection Title]

[Continue with additional subsections as needed...]

Mandatory Pages to Generate

The following pages MUST be generated for any project analysis. Adapt titles and content to match the project:

Page	Content	Key Diagrams
Overview	Project introduction, what it is, version, purpose, subsystem map	Subsystem map (flowchart), tech stack (pie)
Getting Started	Installation, building, hello world, sample apps	Build pipeline (flowchart)
Core Architecture	Main class hierarchy, design patterns, layers	Class hierarchy (classDiagram), layers (graph TD)
Window/UI System	Window classes, control hierarchy, event handling	Class diagram, event sequence diagram
Data Access Layer	Database connectivity, supported backends, ORMs	ER diagram, component dependency
UI Controls	Major controls (grids, inputs, menus, etc.) breakdown	Component relationship diagram
AI and Modern Features	AI integrations, web tech, modern additions	Dependency diagram
Build and Platform Support	Compilers, targets, makefiles, platform matrix	Build pipeline (flowchart)

Style Guidelines for Prose

Write like a wiki article, NOT like a technical report with bullet lists
Use flowing paragraphs that explain concepts naturally
Start each page with a summary paragraph that gives context
Use cross-references to other pages: "For more details see Core Architecture"
Cite source files inline: "The framework version is defined in include/fivewin.ch#L8-9"
Show code snippets indented or in fenced blocks when illustrating specific definitions
Use tables for structured comparisons (compiler matrix, component lists, etc.)
Every page should have a "Relevant source files" blockquote at the top
Keep an academic/encyclopedic tone — informative, neutral, precise

HTML Output Generation

The skill can generate a standalone HTML file that replicates the DeepWiki dark-theme interface. This is the preferred output format when the user requests a visual, browsable wiki.

Files Involved

File	Purpose
`deepwiki-template.html`	Self-contained HTML template with dark theme, 3-column layout (sidebar, content, TOC), Mermaid.js rendering, highlight.js syntax highlighting, search, and responsive design
`md2html.js`	Node.js script that converts the skill's Markdown output into a standalone HTML file using the template

When to Generate HTML

When the user explicitly asks for HTML output
When the user mentions "like DeepWiki" or "visual wiki"
When doing a full repository analysis (the default output should include HTML)
When the user asks to "see" or "browse" the documentation

Method 1: Using the Conversion Script

After generating the Markdown analysis, run:

node md2html.js analysis.md output.html --repo-owner=OwnerName --repo-name=RepoName

The script will:

Extract the ## 📑 Navigation block to build the sidebar
Convert [quote][mermaid]...[/mermaid][/quote] to <div class="mermaid"> for rendering
Split content at --- dividers into separate wiki pages
Generate TOC from h2/h3 headings for the right sidebar
Inject everything into the template and produce a single, self-contained HTML file

Method 2: Direct HTML Generation (Preferred)

The agent can also generate the HTML directly by:

Reading deepwiki-template.html as a reference for the structure and CSS
Replacing the {{PLACEHOLDERS}} with generated content:
- {{REPO_OWNER}} — Repository owner/organization name
- {{REPO_NAME}} — Repository name
- {{NAV_ITEMS}} — HTML for the sidebar navigation tree
- {{PAGE_CONTENT}} — HTML for all wiki pages wrapped in <div class="wiki-page"> elements
- {{TOC_ITEMS}} — HTML for the right-side "On this page" links
Writing the complete HTML file to the output location

Template Placeholder Details

`{{NAV_ITEMS}}` — Sidebar Navigation

Each navigation item uses this structure:

<div class="nav-section">
    <a class="nav-item" data-page="page-overview" onclick="navigateTo('page-overview')">
        <svg class="nav-icon" viewBox="0 0 16 16" fill="currentColor">...</svg>
        Overview
    </a>
</div>

For nested items, increase padding-left in increments of 20px (36px, 56px, etc.).

`{{PAGE_CONTENT}}` — Wiki Pages

Each page is wrapped in a div. The first page should have the active class:

<div class="wiki-page active" id="page-overview">
    <h1>Overview</h1>
    <div class="source-files-box" onclick="toggleSourceFiles(this)">
        <span class="icon">📄</span> Relevant source files
        <span class="chevron">›</span>
    </div>
    <div class="source-files-list">
        <a class="source-file-item" href="#">include/fivewin.ch#L8-9</a>
    </div>
    <p>Page content here...</p>
    <div class="mermaid">
        graph TD
            A["Layer 1"] --> B["Layer 2"]
    </div>
</div>
<div class="wiki-page" id="page-getting-started">
    ...
</div>

`{{TOC_ITEMS}}` — Table of Contents

<a class="toc-link" href="#section-id">Section Title</a>
<a class="toc-link depth-3" href="#subsection-id">Subsection Title</a>

CSS Classes Reference

Class	Usage
`.wiki-page`	Wrapper for each page section, use `.active` to show
`.source-files-box`	Collapsible "Relevant source files" header
`.source-files-list`	Container for source file links
`.source-file-item`	Individual source file link
`.mermaid`	Mermaid diagram container (auto-rendered by Mermaid.js)
`.nav-item`	Sidebar navigation item, use `.active` for current page
`.nav-children`	Collapsible child nav container, use `.open` to expand
`.toc-link`	Right sidebar TOC link, use `.depth-3` for h3 indentation
`.code-block-wrapper`	Auto-generated wrapper for code blocks with copy button

Design Specifications

The template faithfully replicates the DeepWiki interface:

Element	Specification
Background	`#0d1117` (base), `#161b22` (surface), `#1c2129` (overlay)
Text	`#e6edf3` (primary), `#8b949e` (secondary), `#6e7681` (tertiary)
Accent	`#1f6feb` (blue), `#3fb950` (green), `#58a6ff` (links)
Font	Inter (sans), JetBrains Mono (code) — loaded from Google Fonts CDN
Sidebar width	280px (left), 220px (right TOC)
Content max-width	820px
Header height	48px
Mermaid theme	Dark mode with matching color variables
Responsive	TOC hidden at 1200px, sidebar collapses at 768px

Language Handling

The skill:

Detects the language of the user's query automatically
Responds in the SAME language as the user's query
IMPORTANT: If a specific language is requested in the prompt, that language takes priority over the detected query language
Maintains linguistic consistency across ALL iterations in Deep Research mode
Never switches language mid-iteration
Code comments and technical terms may remain in the original language of the codebase

Formatting Rules

All responses must:

Use structured Markdown with proper syntax for all formatting
For code blocks, use triple backticks with language specification (```harbour, ```c, ```javascript, etc.)
Use ## headings for major sections
Use bullet points or numbered lists where appropriate
Format tables using markdown table syntax when presenting structured data
Use bold and italic for emphasis
Reference file paths as inline code
Maintain visual clarity
Include emoji indicators for priority levels (🔴🟡🟢)

Mermaid Diagram Syntax (MANDATORY)

ALL Mermaid diagrams MUST use this custom syntax:

[quote][mermaid]
...mermaid code here (raw, WITHOUT ```mermaid fences)...
[/mermaid][/quote]

Rules:

NEVER use ```mermaid ``` fences for diagrams
ALWAYS wrap Mermaid code inside [quote][mermaid]...[/mermaid][/quote]
The Mermaid code goes directly between the tags, with NO additional code fences
Generate as many Mermaid diagrams as possible to visually illustrate the analysis
Every architecture section, class hierarchy, data flow, build pipeline, event system, and component relationship SHOULD have an accompanying Mermaid diagram

Correct example:

[quote][mermaid]
classDiagram
    class TWindow {
        +hWnd
        +Paint()
        +End()
    }
    TWindow <|-- TDialog
    TWindow <|-- TControl
[/mermaid][/quote]

INCORRECT example (DO NOT do this):

```mermaid
classDiagram
    class TWindow { ... }
```

Critical formatting constraints:

Do NOT include ```markdown fences at the beginning or end of the answer
Start the response directly with the content
The content will already be rendered as markdown, so just provide the raw markdown content
Think step by step and ensure the answer is well-structured and visually organized

Focus Enforcement

The skill guarantees:

Exclusive focus on the queried topic
Continuity in multi-turn investigations
Technical coherence between iterations
Avoidance of topic drift
Responses directly aligned with the original question
If the topic is about a specific file or feature, ONLY that file or feature is analyzed
General repository information is excluded unless directly relevant to the query
NEVER responds with just filler phrases like "Continue the research" — always provides substantive findings
Cross-references previous iteration findings to build a coherent narrative

Mermaid Diagram Guidelines

The analysis MUST generate as many Mermaid diagrams as possible. Below are the mandatory diagram types to include when applicable. All diagrams use [quote][mermaid]...[/mermaid][/quote] syntax.

1. Class Hierarchy Diagram

Use classDiagram to show inheritance and composition between classes:

2. Architecture Layers Diagram

Use graph TD (top-down) to show layered architectures:

3. Data Flow Diagram

Use flowchart LR (left-right) to show how data moves through the system:

4. Build Pipeline Diagram

Use flowchart LR to illustrate the build process and toolchain:

5. Component Dependency Diagram

Use graph LR to show dependencies between modules:

6. Event / Callback Flow Diagram

Use sequenceDiagram to show event handling and callback patterns:

[quote][mermaid] sequenceDiagram participant User participant Window participant Control participant EventHandler

User->>Window: Click/KeyPress
Window->>Control: WndProc dispatch
Control->>EventHandler: Evaluate bAction/bWhen
EventHandler-->>Control: Result
Control-->>Window: Refresh/Update
Window-->>User: Visual feedback

[/mermaid][/quote]

7. Design Patterns Diagram

Use classDiagram to illustrate identified design patterns:

8. Technology Stack Diagram

Use pie or mindmap to show technology distribution:

[quote][mermaid] pie title Code Distribution by Language "Harbour/xBase" : 460 "C" : 200 "C++" : 40 "Headers" : 102 [/mermaid][/quote]

9. State Diagram

Use stateDiagram-v2 to model lifecycle states of key objects:

10. ER Diagram (Data Model)

Use erDiagram when the project has database entities:

[quote][mermaid] erDiagram CUSTOMER ||--o{ ORDER : places ORDER ||--|{ LINE_ITEM : contains PRODUCT ||--o{ LINE_ITEM : "ordered in" [/mermaid][/quote]

When to Include Each Diagram

Diagram Type	When to Include
Class Hierarchy	Always (if the project has classes)
Architecture Layers	Always (for any multi-layered project)
Data Flow	When data processing pipelines exist
Build Pipeline	When the build system is non-trivial
Component Dependencies	When there are 3+ distinct modules
Event/Callback Flow	When event-driven patterns are used
Design Patterns	When recognizable patterns are found
Technology Stack	Always (pie chart of code distribution)
State Diagram	When objects have clear lifecycle states
ER Diagram	When database entities are present

Usage Examples

Full analysis of an unknown project

Analyze the repository at /workspace/my-project as DeepWiki would

Focus on a specific aspect

Perform an architecture analysis of the project focusing on design patterns

Comparison with best practices

Evaluate the code quality comparing with clean code principles

Deep research on a specific module

Investigate the database connectivity layer in depth using Deep Research mode

Quick question about a file

What does the TXBrowse class do and what are its main methods?

Metrics to Collect

Number of files per language
Total lines of code
Maximum directory depth
Number of direct dependencies
Test coverage (if applicable)
Average cyclomatic complexity
Average number of functions/classes per file
Largest files by line count
Class inheritance depth
Number of samples/examples

Prompt Template Reference

For integration with embedding/RAG pipelines, the context processing follows this template structure:

<START_OF_SYS_PROMPT>
{system_prompt}
{output_format_str}
<END_OF_SYS_PROMPT>

{# If conversation history exists #}
<START_OF_CONVERSATION_HISTORY>
{for each dialog_turn in conversation_history}
  {turn_number}.
  User: {user_query}
  You: {assistant_response}
{end for}
<END_OF_CONVERSATION_HISTORY>

{# If file contexts are provided #}
<START_OF_CONTEXT>
{for each context in contexts}
  {index}.
  File Path: {context.file_path}
  Content: {context.text}
{end for}
<END_OF_CONTEXT>

<START_OF_USER_PROMPT>
{user_input}
<END_OF_USER_PROMPT>

Deep Research iterations use role/guidelines/style blocks:

<role>
  Expert analyst identity, repository info, language constraint, iteration context
</role>

<guidelines>
  Iteration-specific behavioral rules (first / intermediate / final)
</guidelines>

<style>
  Output formatting preferences (concise, markdown, citations)
</style>

This structure ensures consistent behavior whether the skill is invoked as a standalone agent, integrated with a semantic search engine, or orchestrated through a multi-turn pipeline.

Available Helper Scripts

The skill includes optional Harbour scripts that can be used during the analysis:

analyze-structure.prg: Analyzes the directory structure and generates a tree with file counts and sizes
detect-tech-stack.prg: Detects technologies based on file extensions and configuration files
calculate-metrics.prg: Calculates code metrics (lines per language, file counts, directory depth)

analyze-structure.prg

/*
 * Directory Structure Analyzer
 * Usage: analyze-structure <path> [max_depth]
 * Generates a visual tree of the directory structure
 */

#include "directry.ch"

FUNCTION Main( cPath, cMaxDepth )

   LOCAL nMaxDepth := 3

   DEFAULT cPath     := "."
   DEFAULT cMaxDepth := "3"

   nMaxDepth := Val( cMaxDepth )

   ? "Directory Structure Analysis"
   ? Replicate( "=", 40 )
   ? ""

   AnalyzeDir( cPath, 0, nMaxDepth )

RETURN NIL

STATIC FUNCTION AnalyzeDir( cPath, nLevel, nMaxDepth )

   LOCAL aFiles, aFile
   LOCAL nFiles := 0, nDirs := 0
   LOCAL cIndent := Replicate( "  ", nLevel )

   IF nLevel > nMaxDepth
      RETURN NIL
   ENDIF

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF

      IF "D" $ aFile[ F_ATTR ]
         nDirs++
         ? cIndent + "[DIR] " + aFile[ F_NAME ]
         AnalyzeDir( cPath + "\" + aFile[ F_NAME ], nLevel + 1, nMaxDepth )
      ELSE
         nFiles++
      ENDIF
   NEXT

   ? cIndent + "  (" + LTrim( Str( nFiles ) ) + " files, " + ;
     LTrim( Str( nDirs ) ) + " subdirs)"

RETURN NIL

detect-tech-stack.prg

/*
 * Technology Stack Detector
 * Usage: detect-tech-stack <path>
 * Detects programming languages and frameworks from file extensions
 * and configuration files
 */

FUNCTION Main( cPath )

   LOCAL aExtensions := {}
   LOCAL aTechFiles  := { ;
      { "package.json",     "Node.js / JavaScript" }, ;
      { "pyproject.toml",   "Python"               }, ;
      { "Cargo.toml",       "Rust"                  }, ;
      { "pom.xml",          "Java (Maven)"          }, ;
      { "build.gradle",     "Java (Gradle)"         }, ;
      { "Makefile",         "Make build system"     }, ;
      { "Dockerfile",       "Docker"                }, ;
      { "docker-compose.yml", "Docker Compose"      }, ;
      { ".hbp",             "Harbour"               }, ;
      { "fivewin.ch",       "FiveWin for Harbour"   }, ;
      { "tsconfig.json",    "TypeScript"            }, ;
      { "webpack.config.js","Webpack"               }, ;
      { "go.mod",           "Go"                    }, ;
      { "CMakeLists.txt",   "CMake"                 }, ;
      { ".csproj",          "C# / .NET"             }  ;
   }

   DEFAULT cPath := "."

   ? "Technology Stack Detection"
   ? Replicate( "=", 40 )
   ? ""

   // Detect by config files
   ? "## Detected Technologies"
   DetectByConfigFiles( cPath, aTechFiles )

   ? ""
   ? "## Languages by Extension"
   CountByExtension( cPath, aExtensions )

RETURN NIL

STATIC FUNCTION DetectByConfigFiles( cPath, aTechFiles )

   LOCAL aItem

   FOR EACH aItem IN aTechFiles
      IF File( cPath + "\" + aItem[ 1 ] ) .OR. ;
         File( cPath + "\include\" + aItem[ 1 ] )
         ? "  [✓] " + aItem[ 2 ] + " (" + aItem[ 1 ] + ")"
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountByExtension( cPath, aExtensions )

   LOCAL aLangs := { ;
      { ".prg", "Harbour/xBase", 0 }, ;
      { ".c",   "C",             0 }, ;
      { ".cpp", "C++",           0 }, ;
      { ".h",   "C/C++ Header",  0 }, ;
      { ".ch",  "Clipper Header", 0 }, ;
      { ".js",  "JavaScript",    0 }, ;
      { ".ts",  "TypeScript",    0 }, ;
      { ".py",  "Python",        0 }, ;
      { ".rb",  "Ruby",          0 }, ;
      { ".go",  "Go",            0 }, ;
      { ".rs",  "Rust",          0 }, ;
      { ".java","Java",          0 }, ;
      { ".cs",  "C#",            0 }, ;
      { ".bat", "Batch script",  0 }, ;
      { ".sh",  "Shell script",  0 }, ;
      { ".md",  "Markdown",      0 }, ;
      { ".html","HTML",          0 }, ;
      { ".css", "CSS",           0 }  ;
   }
   LOCAL aItem

   CountFilesRecursive( cPath, aLangs )

   FOR EACH aItem IN aLangs
      IF aItem[ 3 ] > 0
         ? "  " + PadR( aItem[ 2 ], 20 ) + LTrim( Str( aItem[ 3 ] ) ) + " files"
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountFilesRecursive( cPath, aLangs )

   LOCAL aFiles, aFile, aItem, cExt

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF
      IF "D" $ aFile[ F_ATTR ]
         IF aFile[ F_NAME ] != ".git"
            CountFilesRecursive( cPath + "\" + aFile[ F_NAME ], aLangs )
         ENDIF
      ELSE
         cExt := Lower( SubStr( aFile[ F_NAME ], RAt( ".", aFile[ F_NAME ] ) ) )
         FOR EACH aItem IN aLangs
            IF cExt == aItem[ 1 ]
               aItem[ 3 ]++
               EXIT
            ENDIF
         NEXT
      ENDIF
   NEXT

RETURN NIL

calculate-metrics.prg

/*
 * Code Metrics Calculator
 * Usage: calculate-metrics <path>
 * Calculates lines of code, file counts, and complexity estimates
 */

#include "directry.ch"

STATIC nTotalLines  := 0
STATIC nTotalFiles  := 0
STATIC nMaxDepth    := 0
STATIC nLargestFile := 0
STATIC cLargestName := ""

FUNCTION Main( cPath )

   LOCAL aCodeExts := { ".prg", ".c", ".cpp", ".h", ".ch", ".js", ".ts", ;
                        ".py", ".go", ".rs", ".java", ".cs" }

   DEFAULT cPath := "."

   ? "Code Metrics Report"
   ? Replicate( "=", 40 )
   ? ""

   ProcessDir( cPath, aCodeExts, 0 )

   ? ""
   ? "## Summary"
   ? "  Total source files:  " + LTrim( Str( nTotalFiles ) )
   ? "  Total lines of code: " + LTrim( Str( nTotalLines ) )
   ? "  Max directory depth: " + LTrim( Str( nMaxDepth ) )
   ? "  Largest file:        " + cLargestName + ;
     " (" + LTrim( Str( nLargestFile ) ) + " lines)"

   IF nTotalFiles > 0
      ? "  Avg lines per file:  " + LTrim( Str( Int( nTotalLines / nTotalFiles ) ) )
   ENDIF

RETURN NIL

STATIC FUNCTION ProcessDir( cPath, aCodeExts, nDepth )

   LOCAL aFiles, aFile, cExt, nLines

   IF nDepth > nMaxDepth
      nMaxDepth := nDepth
   ENDIF

   aFiles := Directory( cPath + "\*.*", "D" )

   FOR EACH aFile IN aFiles
      IF aFile[ F_NAME ] == "." .OR. aFile[ F_NAME ] == ".."
         LOOP
      ENDIF
      IF "D" $ aFile[ F_ATTR ]
         IF aFile[ F_NAME ] != ".git" .AND. aFile[ F_NAME ] != "node_modules"
            ProcessDir( cPath + "\" + aFile[ F_NAME ], aCodeExts, nDepth + 1 )
         ENDIF
      ELSE
         cExt := Lower( SubStr( aFile[ F_NAME ], RAt( ".", aFile[ F_NAME ] ) ) )
         IF AScan( aCodeExts, cExt ) > 0
            nTotalFiles++
            nLines := CountLines( cPath + "\" + aFile[ F_NAME ] )
            nTotalLines += nLines
            IF nLines > nLargestFile
               nLargestFile := nLines
               cLargestName := cPath + "\" + aFile[ F_NAME ]
            ENDIF
         ENDIF
      ENDIF
   NEXT

RETURN NIL

STATIC FUNCTION CountLines( cFile )

   LOCAL nHandle, cLine, nCount := 0

   nHandle := FOpen( cFile )

   IF nHandle >= 0
      DO WHILE ! HB_FEof( nHandle )
         cLine := HB_FReadLine( nHandle )
         nCount++
      ENDDO
      FClose( nHandle )
   ENDIF

RETURN nCount

Run any of these scripts with Harbour: hbrun analyze-structure.prg <path>

code-deep-analysis

Deep Code Analysis Skill

When to Use This Skill

Inputs

Outputs

Operation Modes

Mode 1: RAG (Contextual Analysis)

Mode 2: Deep Research (Multi-Turn Investigation)

First Iteration

Intermediate Iterations

Final Iteration

Mode 3: Simple Chat (Direct Response)

How to Run the Analysis

Phase 1: Initial Exploration

Phase 2: Technology Analysis

Phase 3: Architecture Analysis

Phase 4: Code Analysis

Phase 5: Testing and Quality

Phase 6: Report Generation

Decision Tree

Output Format — DeepWiki Page Style

Page Structure Conventions

Sidebar Navigation Structure

Wiki Page Template

Mandatory Pages to Generate

Style Guidelines for Prose

HTML Output Generation

Files Involved

When to Generate HTML

Method 1: Using the Conversion Script

Method 2: Direct HTML Generation (Preferred)

Template Placeholder Details

{{NAV_ITEMS}} — Sidebar Navigation

{{PAGE_CONTENT}} — Wiki Pages

{{TOC_ITEMS}} — Table of Contents

CSS Classes Reference

Design Specifications

Language Handling

Formatting Rules

Mermaid Diagram Syntax (MANDATORY)

Focus Enforcement

Mermaid Diagram Guidelines

1. Class Hierarchy Diagram

2. Architecture Layers Diagram

3. Data Flow Diagram

4. Build Pipeline Diagram

5. Component Dependency Diagram

6. Event / Callback Flow Diagram

7. Design Patterns Diagram

8. Technology Stack Diagram

9. State Diagram

10. ER Diagram (Data Model)

When to Include Each Diagram

Usage Examples

Full analysis of an unknown project

Focus on a specific aspect

Comparison with best practices

Deep research on a specific module

Quick question about a file

Metrics to Collect

Prompt Template Reference

Available Helper Scripts

analyze-structure.prg

detect-tech-stack.prg

calculate-metrics.prg

Deep Code Analysis Skill

When to Use This Skill

Inputs

Outputs

Operation Modes

Mode 1: RAG (Contextual Analysis)

Mode 2: Deep Research (Multi-Turn Investigation)

First Iteration

Intermediate Iterations

Final Iteration

Mode 3: Simple Chat (Direct Response)

How to Run the Analysis

Phase 1: Initial Exploration

Phase 2: Technology Analysis

Phase 3: Architecture Analysis

`{{NAV_ITEMS}}` — Sidebar Navigation

`{{PAGE_CONTENT}}` — Wiki Pages

`{{TOC_ITEMS}}` — Table of Contents

`{{NAV_ITEMS}}` — Sidebar Navigation

`{{PAGE_CONTENT}}` — Wiki Pages

`{{TOC_ITEMS}}` — Table of Contents