You open a new chat.

Then you spend the next few minutes explaining your project.

• Here's the architecture.

• These are the important folders.

• Authentication works like this.

• Don't touch this file.

• We use services instead of controllers.

• Database access goes through Prisma.

• Here's how the payments flow works.

Only after all of that does the actual work begin.

Then you switch to another tool.

Or start another session.

Or come back tomorrow.

And you do it all over again.

The strange part is that nothing about the repository changed.

The knowledge already exists.

It's just trapped inside the developer's head.

We solved package management.

We solved version control.

We solved dependency management.

But we still haven't solved project knowledge.

Every repository already contains enough information to describe itself:

• Its architecture

• Folder conventions

• Dependency graph

• High-risk areas

• Feature boundaries

• Coding rules

• Critical files

Yet every new tool has to rediscover that knowledge from scratch.

That's wasted computation.

More importantly, it's wasted developer time.

The repository should carry its own knowledge.

That idea became the foundation for TokenCap.

Instead of generating prompts, TokenCap builds a persistent knowledge layer alongside your repository.

A knowledge layer that explains:

• How the project is structured

• What matters

• What should never change

• Where specific features live

• Which files belong together

Once that knowledge exists, every new session starts from understanding instead of discovery.

v1.0.0

With v1.0.0, TokenCap generates a self-loading context layer for your repository. It creates an AGENTS.md entry point and supporting project intelligence files so tools can discover the project's structure automatically rather than relying on repeated manual explanations.

The important part isn't the files themselves.

It's the shift in thinking.

Instead of teaching every new tool about your project...

Teach the repository once.

Everything else should learn from it.

Where I think this is going

I don't think the future of software development is writing longer prompts.

I think repositories will become self-describing.

A repository won't just contain source code.

It will also contain its architecture, conventions, boundaries, risks, and accumulated knowledge in a format that any tool can understand.

Code tells us what the software does.

Project intelligence explains how it should evolve.

That's the direction I'm building toward with TokenCap.

TokenCap v1.0.0 is now live.

🌐 https://tokencap.vansharora.app

📦 https://www.npmjs.com/package/tokencap

The issue wasn't the AI model.

The issue was context.

Modern codebases contain thousands of files, dependencies, architectural decisions, business logic, configuration files, debugging history, and undocumented assumptions. Most AI tools only see the small portion of code you manually provide, which often leads to incomplete or inaccurate responses.

To solve this, I started building TokenCap.

TokenCap is a developer tool that helps transform a codebase into structured, AI-ready context.

Instead of manually collecting files and explaining project architecture every time you interact with an AI assistant, TokenCap generates project intelligence automatically.

What TokenCap Does

Project Knowledge Graph

Maps relationships between files, modules, routes, services, components, and dependencies to provide a high-level understanding of the project structure.

Context Memory

Stores important project decisions, architecture notes, constraints, and development history so valuable context isn't lost between development sessions.

Change Intelligence

Converts raw Git diffs into meaningful reports that explain:

• What changed

• Why it matters

• Potential risks

• Impacted areas

• Testing recommendations

Context Packing

Large codebases often exceed practical AI context limits.

TokenCap prioritizes and compresses relevant project information into token-budgeted context packs optimized for debugging, code reviews, and development tasks.

Why I Built It

As AI becomes a bigger part of software development, context is becoming just as important as the model itself.

Developers don't need another chatbot.

They need tools that help AI understand their projects.

That's the direction I'm exploring with TokenCap.

I'm currently working on the next version, which includes an interactive knowledge graph inspired by tools like Obsidian, along with deeper context management capabilities.

If you're building with AI and have faced challenges with context windows, codebase understanding, or token limits, I'd love to hear how you're solving it.

Website: TOKENCAP