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Update document for supported agents
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‎web/content/docs/2-development-with-ai-devkit.md‎

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title: Development with AI DevKit
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description: Learn how to use AI DevKit commands for structured development workflows
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slug: development-with-ai-devkit
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order: 2
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order: 3
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---
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## Start with `/new-requirement`

‎web/content/docs/2-supported-agents.md‎

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---
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title: Supported AI Agents & Environments
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description: Environments supported by AI DevKit
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order: 2
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---
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## Supported Environments
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### [Cursor](https://cursor.com/)
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**What AI DevKit provides:**
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- `AGENTS.md` - Context file with AI agent configurations
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- `.cursor/commands/` - Custom slash commands for structured development workflows
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- `.cursor/rules/` - Editor rules for consistent coding standards
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### [Claude Code](https://www.claude.com/product/claude-code)
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**What AI DevKit provides:**
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- `AGENTS.md` - Claude workspace configuration and context
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- `.claude/commands/` - Command-line tools and scripts optimized for Claude Code
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### [GitHub Copilot](https://github.com/features/copilot)
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**What AI DevKit provides:**
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- `AGENTS.md` - GitHub Copilot configuration and context settings
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- `.github/commands/` - GitHub-integrated workflow commands
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### [Google Gemini](https://geminicli.com/)
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**What AI DevKit provides:**
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- `AGENTS.md` - Gemini configuration with multimodal context
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- `.gemini/commands/` - Commands optimized for Gemini's capabilities
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### [OpenAI Codex](https://chatgpt.com/en-SE/features/codex)
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**What AI DevKit provides:**
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- `AGENTS.md` - Codex-specific configuration and context
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- `.codex/commands/` - Commands tailored for Codex's code-focused capabilities
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### [Windsurf](https://windsurf.com/)
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**What AI DevKit provides:**
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- `AGENTS.md` - Windsurf environment configuration
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- `.windsurf/commands/` - Commands optimized for Windsurf's interface
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### [KiloCode](https://kilocode.ai/)
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**What AI DevKit provides:**
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- `AGENTS.md` - KiloCode configuration for large project handling
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- `.kilocode/commands/` - Commands designed for large-scale development
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### [AMP](https://ampcode.com/)
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**What AI DevKit provides:**
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- `AGENTS.md` - AMP configuration for accelerated workflows
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- `.agents/commands/` - Commands optimized for rapid development cycles
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### [OpenCode](https://opencode.ai/)
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**What AI DevKit provides:**
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- `AGENTS.md` - OpenCode configuration with community features
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- `.opencode/commands/` - Commands leveraging open-source AI improvements
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### [Roo Code](https://roocode.com/)
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**What AI DevKit provides:**
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- `AGENTS.md` - Roo Code configuration and context
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- `.roo/commands/` - Commands optimized for Roo's advanced features
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## Environment Setup
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### Interactive Multi-Selection
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When you run `ai-devkit init`, you can select multiple environments simultaneously:
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```bash
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ai-devkit init
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```
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This presents an interactive checklist where you can:
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- Use spacebar to select/deselect environments
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- Press Enter to confirm your selections
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- Choose any combination of the 10 supported environments
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### Configuration Storage
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Your selections are stored in `.ai-devkit.json`:
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```json
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{
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"version": "0.4.0",
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"environments": ["cursor", "claude", "github"],
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"initializedPhases": ["requirements", "design"],
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"createdAt": "2025-10-31T...",
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"updatedAt": "2025-10-31T..."
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}
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```
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### Re-running Setup
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If you want to add more environments later:
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```bash
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ai-devkit init
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```
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AI DevKit will:
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1. Detect existing environments
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2. Show confirmation prompts for overwriting
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3. Add new environments alongside existing ones
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### Override Protection
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When re-running `ai-devkit init`, you'll be prompted before overwriting existing environment configurations:
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```
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Warning: The following environments are already set up: cursor, claude
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Do you want to continue?
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```
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## Contributing New Environments
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AI DevKit welcomes contributions for new AI development environments. To add support for a new environment:
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1. **Create Environment Definition**: Add to `src/util/env.ts`
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2. **Add Templates**: Create `templates/env/{code}/` directory
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3. **Update Documentation**: Add to this guide
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4. **Test Integration**: Ensure proper initialization and configuration

‎web/content/docs/3-development-with-ai-devkit.md‎

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---
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title: Development with AI DevKit
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description: Learn how to use AI DevKit commands for structured development workflows
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slug: development-with-ai-devkit
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order: 3
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---
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## Start with `/new-requirement`
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The `/new-requirement` command is your entry point for any new feature development. It guides you through a complete development lifecycle:
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```bash
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# In Cursor or Claude Code
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/new-requirement
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```
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**What happens:**
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1. **Requirements Capture** - Define what you're building and why
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2. **Design Phase** - Create architecture and technical specifications
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3. **Planning** - Break down work into actionable tasks
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4. **Implementation** - Step-by-step coding with guidance
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5. **Testing** - Generate comprehensive test coverage
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6. **Git Workflow** - Structured commits and PR creation
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**Generated Documentation:**
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- `docs/ai/requirements/feature-{name}.md` - Requirements and user stories
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- `docs/ai/design/feature-{name}.md` - Architecture and technical design
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- `docs/ai/planning/feature-{name}.md` - Task breakdown and timeline
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- `docs/ai/implementation/feature-{name}.md` - Implementation notes
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- `docs/ai/testing/feature-{name}.md` - Test strategy and cases
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### Refine Your Work
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**Review Requirements:**
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```bash
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/review-requirements
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```
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Validates completeness and identifies gaps in your requirements.
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**Review Design:**
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```bash
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/review-design
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```
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Ensures architecture clarity and generates Mermaid diagrams.
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**Execute Your Plan:**
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```bash
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/execute-plan
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```
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Interactive task execution that:
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- Reads your planning document
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- Presents tasks in logical order
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- Captures progress and notes
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- Prompts documentation updates
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**Code Review:**
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```bash
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/code-review
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```
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Pre-commit review that checks:
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- Alignment with design documents
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- Logic, security, and performance issues
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- Code redundancy and missing tests
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- Documentation completeness
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**Generate Tests:**
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```bash
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/writing-test
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```
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Creates unit and integration tests targeting high coverage.

‎web/content/docs/3-understand-existing-code-with-ai-devkit.md‎

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---
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title: Understanding Existing Code with AI DevKit
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description: Learn how to analyze and document existing codebases using AI DevKit's capture-knowledge command
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order: 4
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---
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## Use `/capture-knowledge` for Code Analysis

‎web/content/docs/4-debugging-with-ai-devkit.md‎

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---
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title: Debugging with AI DevKit
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description: Learn how to systematically debug issues using AI DevKit's structured debugging workflows
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---
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## Use `/debug` for Systematic Problem Solving

‎web/content/docs/5-understand-existing-code-with-ai-devkit.md‎

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---
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title: Understanding Existing Code with AI DevKit
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description: Learn how to analyze and document existing codebases using AI DevKit's capture-knowledge command
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order: 4
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---
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## Use `/capture-knowledge` for Code Analysis
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When working with existing codebases, the `/capture-knowledge` command helps you understand complex systems by analyzing code from any entry point and generating comprehensive documentation with visual diagrams.
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```bash
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# In Cursor
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/capture-knowledge <entry-point> [options]
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# In Claude Code
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Use the capture-knowledge command to analyze <entry-point>
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```
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### Entry Point Types
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**Files:**
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```bash
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/capture-knowledge src/api/users.ts
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```
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Analyzes a specific file and its dependencies.
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**Folders:**
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```bash
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/capture-knowledge src/services/
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```
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Analyzes an entire module or directory structure.
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**Functions:**
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```bash
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/capture-knowledge calculateTotalPrice
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```
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Analyzes a specific function and its call chain.
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**API Endpoints:**
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```bash
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/capture-knowledge POST:/api/users
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```
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Analyzes complete API request/response flow.
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### What You Get
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**Detailed Explanations**
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- Natural language descriptions of how code works
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- Implementation details and design patterns
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- Logic flow and component relationships
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**Recursive Analysis**
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- Automatically traces all dependencies
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- Maps complete execution paths
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- Identifies external integrations
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**Visual Diagrams**
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- Flowcharts showing execution paths
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- Sequence diagrams for API flows
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- Architecture diagrams for modules
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- Component relationship maps
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**Actionable Insights**
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- Performance considerations
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- Security implications
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- Potential improvements
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- Refactoring opportunities
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### Use Cases
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- **Onboarding** - Help new developers understand complex systems
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- **Documentation** - Generate comprehensive system documentation
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- **Debugging** - Understand complete execution flows
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- **Refactoring** - Get full context before making changes
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- **Knowledge Base** - Create searchable documentation
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**Output Location:** Analysis is saved to `docs/ai/knowledge/` and can be versioned with your code.

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