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Enhance documentation and configuration: add JSON Schema guide, update navigation links, and introduce CaC and CDD concepts
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docs/.vitepress/config.mts

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@@ -25,24 +25,27 @@ export default withMermaid({
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text: 'Home',
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link: '/',
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items: [
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{text: 'What is CTX?', link: '/'},
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{text: 'Quick Start', link: '/quick-start'},
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{text: 'Understanding CaC, CDD', link: '/cdd'}
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]
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},
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{
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text: 'Getting Started',
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items: [
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{text: 'Installation', link: '/getting-started'},
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{text: 'Configuration', link: '/configuration'},
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{text: 'Configuration', link: '/getting-started/configuration'},
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{text: 'Json Schema', link: '/getting-started/json-schema'},
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{text: 'Command Reference', link: '/getting-started/command-reference'},
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{text: 'Variables in Configuration', link: '/variables'},
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{text: 'Variables in Configuration', link: '/getting-started/variables'},
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{text: 'IDE Integration', link: '/getting-started/ide-integration'},
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{text: 'Logging', link: '/advanced/logging'}
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{text: 'Logging', link: '/getting-started/logging'}
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]
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},
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{
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text: 'MCP Server',
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items: [
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{text: 'Integration', link: '/mcp-server'},
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{text: 'Integration', link: '/mcp'},
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{text: 'Filesystem', link: '/mcp/filesystem'},
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{text: 'Prompts', link: '/mcp/prompts'},
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{text: 'Tools', link: '/mcp/tools'},

docs/cdd.md

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# Understanding CaC, CDD
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## Context as Code (CaC)
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Context as Code (CaC) is an approach where code, documentation, and structure serve as explicit context for both humans
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and AI systems, making the codebase more comprehensible and maintainable.
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### Key principles of CaC:
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1. **Structured Documentation**: Code is organized with meaningful comments, examples, and well-structured organization
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to make it a rich source of context.
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2. **Contextual Awareness**: The code and its documentation together provide sufficient context for understanding the
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system's architecture and design decisions.
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3. **Focus on Comprehensibility**: Documentation isn't separate from code but integrated as part of the codebase,
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ensuring it remains up-to-date.
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> For the CaC approach (Context as Code, describing context with code) to work well, signatures alone aren't always
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> enough. And that's how comments appear in your code. Not those that just repeat method or class names, but meaningful
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> ones with examples.
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## Claude (Context) Driven Development (CDD)
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CDD is a development methodology where an AI assistant like Claude helps generate and review code based on
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well-structured context, with humans providing guidance and final approval.
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### CDD workflow:
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1. Provide relevant context to the LLM
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2. Define requirements or feature requests
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3. Collaborate with the LLM to refine the approach
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4. Generate code with the LLM
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5. Review and refine the code
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6. Add tests, documentation and finalize
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**Benefits:**
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- Automatic comment updates for changed functions
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- Excellent unit test generation
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- Reduced procrastination by offloading routine tasks
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- Developer focus on more interesting parts of code
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## CTX: The Bridge Between CaC and CDD
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CTX is the tool that connects the principles of CaC with the CDD workflow. It automates the process of gathering and
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structuring context from code to feed into LLMs like Claude.
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### How CTX supports CaC and CDD:
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1. **Context Generation**: CTX automatically builds organized context files from various sources (code files, GitHub
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repositories, git diffs, web pages, etc.).
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2. **Structured Documentation**: As described in the documents, CTX creates well-formatted markdown documents containing
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all relevant context about the codebase.
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3. **Modifiers for Optimization**: CTX includes modifiers that transform source content to make it more useful for LLM
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contexts, supporting the CaC principle of making code self-documenting.
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4. **MCP Server Integration**: CTX provides a built-in MCP (Model Control Protocol) server that allows Claude to
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directly access project information, enabling a more seamless CDD workflow.
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### The Connection Between These Concepts:
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The quality of LLM-based tools depends on the quality of context. And you can improve context quality using LLMs.
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1. Well-structured code with good documentation (CaC) provides better context for LLMs
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2. LLMs with good context can write better code and documentation (CDD)
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3. This improved code and documentation further enhances the context (CaC)
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4. CTX automates the process of collecting and formatting this context
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## Practical Implementation with CTX
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CTX facilitates CaC and CDD with specific features:
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1. **Document Generation**: CTX creates markdown documents with compiled content from various sources, organizing
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related code and context in a single file.
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2. **Source Management**: CTX can pull from files, GitHub repositories, git diffs, and other sources to provide
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comprehensive context.
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3. **Modifiers**: CTX transforms content to make it more useful, including extracting signatures, filtering content, and
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generating documentation.
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4. **Prompts**: CTX allows defining reusable prompts for common tasks, enhancing the CDD workflow.
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5. **Tools Integration**: Custom tools can be executed directly by the LLM during conversations, enabling more
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sophisticated interactions.
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## Benefits for Development
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The combined approach of CaC, CDD, and CTX yields significant benefits:
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1. **Better Code Structure**: As mentioned in the article, "Programming with contexts forces you to structure code
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properly" - a positive side effect of preparing code for AI interaction.
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2. **Maintained Documentation**: The CDD process keeps documentation current as Claude updates comments for functions it
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changes.
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3. **Faster Development**: The article mentions completing features in about 2 hours that would have taken longer
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manually.
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4. **Reduced Cognitive Load**: The author notes they "can parallel CDD with watching conference talks" because writing
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prompts doesn't require getting into a flow state.
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5. **Focus on Interesting Problems**: By giving routine tasks to LLMs, developers can focus on the most interesting and
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challenging aspects of development.
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This integrated approach represents a new paradigm in software development where human creativity and AI capabilities
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complement each other, with tools like CTX serving as the crucial bridge between well-structured code and AI assistance.
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