The Context Gap in AI-Assisted Development

As AI coding assistants like ChatGPT become indispensable co-pilots for developers, a critical challenge persists: How do you efficiently convey complex project structures to an AI? Pasting individual files is cumbersome, while describing architecture manually is error-prone. Enter PromptMap—a .NET console application that automates contextual mapping for seamless AI collaboration.

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How PromptMap Bridges the AI-Developer Divide

PromptMap scans Visual Studio .sln files or directories of .cs files, generating a structured hierarchy of namespaces, classes, methods, and properties. Unlike traditional documentation tools, its output is optimized for AI consumption—concise yet comprehensive. Key features include:

  • Recursive directory/solution parsing
  • Configurable inclusion of private members and constructors
  • Output to file or stdout
  • Zero external dependencies (runs entirely locally)

Developers launch it via CLI:

promptmap --solution MyProject.sln --include-private --out ai_context.txt

The Technical Engine: Roslyn-Powered Analysis

Under the hood, PromptMap leverages Microsoft's Roslyn compiler platform to analyze C# syntax trees. The RoslynWalker class processes semantic models to build a Node-based representation of the codebase. This tree structure preserves relationships between entities while filtering noise—critical for keeping AI prompts focused.

Example output for a UserService class:

MyApp.Services
└─ UserService
   ├─ Method User GetById(int id) [public]
   ├─ Method void Update(User user) [public]
   └─ Property ILogger Logger { get; } [private]

Why This Changes the Game for .NET Developers

  1. Precision in AI Queries: Feeding PromptMap's output to ChatGPT yields more accurate refactoring suggestions, bug fixes, and feature implementations—the AI "sees" your entire architecture.
  2. Onboarding Acceleration: New team members (human or AI) grasp project structure in seconds.
  3. Security Compliance: With no cloud dependencies, proprietary code never leaves your machine.

As AI coding tools evolve, solutions like PromptMap highlight a paradigm shift: The future isn't just about smarter AIs—it's about smarter context handoffs between humans and machines. By automating this bridge, developers reclaim hours previously lost to manual context-setting, pushing more focus to creative problem-solving.