AI documentation clarity

Ensure AI-related documentation, comments, and explanations are clear, accurate, and well-structured. This includes fixing spelling errors, using precise terminology, adding necessary context about experimental features, and employing active voice for better readability.

Key practices:

• Fix spelling errors immediately (e.g., “asynchronous” not “asyncronous”) as they can block merges
• Use precise, professional language (“preferred” instead of “favorite”)
• Add context and links for technical concepts (e.g., link to MCP documentation when mentioning Model Context Protocol)
• Use active voice for clearer explanations (“You can configure LLM APIs” instead of “LLM APIs can be configured”)
• Simplify complex technical explanations while maintaining accuracy
• Mark experimental features clearly to set proper expectations

Example improvement:

// Before: "LLM APIs can be configured to return structured data"
// After: "You can configure LLM APIs to return structured data"

// Before: "The Angular CLI includes a Model Context Protocol (MCP) server"
// After: "The Angular CLI includes an experimental [Model Context Protocol (MCP) server](https://modelcontextprotocol.io/)"

Clear documentation is especially critical for AI features as they often involve complex concepts, experimental APIs, and emerging patterns that developers may be unfamiliar with.