Give Your AI a Map, Not a Code Dump

Claude confidently wrote import { db } from './database' for my project last week. That file doesn't exist. My database lives at @/lib/db, and I have 10 tables Claude didn't know about — because I never told it.

This is the problem nobody talks about with AI coding assistants. They can write algorithms, refactor code, generate tests — but they're working blind. They don't know your file structure, your import conventions, or which of your 10 database tables actually exist. So they guess. And you spend 20 minutes fixing what was supposed to save you time.

The Context Problem

This isn't about AI being dumb — it's about AI being blind. When you paste a snippet of code into Claude or Cursor, the AI sees text, not architecture. It doesn't know that @/lib/utils is the most imported module in your project, used in 12 different files. It doesn't know your routing patterns or your database schema.

So it fills in the gaps with plausible-sounding guesses. Hallucinated imports. Non-existent file paths. Components that don't match your design system.

Why Code Dumps Don't Work

The obvious fix seems simple: just give the AI more code. Paste your whole project. Some tools even automate this, concatenating your entire codebase into one massive file and dumping it into the prompt.

This doesn't work for two reasons.

First, it wastes tokens. A typical project has thousands of lines of code. Most of it is implementation detail the AI doesn't need. You're burning context window on the body of every function when the AI only needs to know the function exists, what it's called, and where it lives.

Second, and more importantly, raw code isn't understanding. Think of it this way: if you asked someone to write a chapter for your novel, would you hand them a dictionary? Or would you give them an outline — the characters, the plot structure, the themes, the style guide? The AI needs a map of your project, not the full territory.

The Solution: Structured Context

This is the idea behind Orbit — a free, open-source CLI that scans your codebase and generates a structured context file that AI assistants actually understand.

Instead of dumping raw code, Orbit produces a concise "blueprint" of your project: your tech stack, page routes, API endpoints, database schema, export catalog, and — crucially — your import graph. It tells the AI which modules are the hubs of your codebase, so it knows the right way to import things.

Here's what a generated CLAUDE.md looks like for a real Next.js SaaS project:

# Project: example-nextjs-saas

## Tech Stack
React 19.0.0 / TypeScript / Tailwind CSS / Drizzle ORM

## Project Structure
- **Pages (4):** /dashboard /login /pricing /settings
- **API Routes (11):** GET, POST, PUT, PATCH
- **DB Tables (9):** users, sessions, teams, team_members, products,
  orders, order_items, subscriptions, audit_logs

## Key Files
- Largest: schema.ts (85 lines), billing-settings.tsx (34 lines),
  pricing-table.tsx (33 lines)
- 38 source files, ~848 lines

## Exports
- **Components (22):** DashboardPage, RootLayout, LoginPage,
  PricingPage, ProductList, RecentOrders, RevenueChart, StatsCards,
  Hero, PricingTable, BillingSettings, TeamSettings, Navbar, Sidebar...
- **Functions (27):** useAuth, useLogout, useOrders, useOrderStats,
  useProducts, useCreateProduct, useTeam, getSession...
- **Types (14):** DB, CreateProductInput, CreateOrderInput, User,
  Team, Product, Order, Subscription, UserRole, OrderStatus...

## Import Graph
35 files, 81 local imports

Most imported modules:
- `@/lib/utils` (12 imports)
- `@/types` (10 imports)
- `@/lib/auth` (7 imports)
- `@/components/ui/button` (7 imports)
- `@/components/ui/card` (7 imports)
- `@/db` (6 imports)
- `@/db/schema` (6 imports)

## Environment Variables
DATABASE_URL, NEXT_PUBLIC_URL, STRIPE_SECRET_KEY,
STRIPE_WEBHOOK_SECRET

Look at what the AI now knows without seeing a single line of implementation code:

• The project uses Drizzle ORM, not Prisma — so it won't generate Prisma client calls.
• The database connection is at @/db, not ./database or lib/prisma.
• There are 9 specific tables, so the AI knows orders exists but invoices doesn't.
• @/lib/utils is the most-used module — the AI will import from there, not reinvent utilities.
• The project uses @/components/ui/button, signaling a component library convention.

This is the difference between an AI that guesses and one that knows.

How to Use It

npm i -g @orbit-cli/core

Then, in your project root:

orbit scan -g

That's it. One command. Orbit scans your project and generates a CLAUDE.md file in your project root. Claude Code, Cursor, Copilot, and Windsurf all automatically pick up their respective context files.

Want a different format? Orbit supports multiple output targets:

orbit scan -g --target cursor    # generates .cursorrules
orbit scan -g --target copilot   # generates copilot-instructions.md
orbit scan -g --target windsurf  # generates .windsurfrules

No account required. No auth. No config files. Just scan and go.

Before vs After

Here's a concrete example. Say you ask Claude: "Add a new API endpoint to update a team member's role."

Without context, Claude might generate:

// app/api/teams/update-role/route.ts
import { prisma } from '@/lib/prisma'

export async function POST(req: Request) {
  const { userId, role } = await req.json()
  const updated = await prisma.teamMember.update({
    where: { userId },
    data: { role }
  })
  return Response.json(updated)
}

Three problems: wrong ORM (Prisma instead of Drizzle), wrong import path, and it used POST where your existing pattern uses PATCH for updates.

With Orbit context, Claude knows the project uses Drizzle ORM, that the database is at @/db, that the schema is at @/db/schema, and that the existing API pattern uses PATCH for updates. It generates:

// app/api/teams/members/route.ts
import { db } from '@/db'
import { team_members } from '@/db/schema'
import { eq } from 'drizzle-orm'

export async function PATCH(req: Request) {
  const { userId, role } = await req.json()
  const [updated] = await db
    .update(team_members)
    .set({ role })
    .where(eq(team_members.userId, userId))
    .returning()
  return Response.json(updated)
}

Correct ORM. Correct imports. Correct HTTP method. Code that actually works on the first try.

Try It

npm i -g @orbit-cli/core
cd your-project
orbit scan -g

Give your AI assistant the context it needs. Stop fixing hallucinated imports.

If you find it useful, star it on GitHub — it helps others discover the project.

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Orbit is 100% free and MIT licensed. Works with Next.js, React, Vue, Express, and more.