Describe a feature. Ship it complete.

Scope analyzes your codebase and turns a plain-English description into implementation-ready tickets your AI coding tool can execute — so nothing gets missed.

Works with Claude Code, Cursor, Codex, and any MCP-compatible tool.

Scope conversation
Codebase connected

AI agents build 60% of a feature and call it done

Without codebase context, AI tools miss integrations, skip edge cases, and leave you filling in the gaps. Scope fixes that.

Before

Incomplete output, expensive rework

Your AI builds the core and stops

It handles the happy path but misses lifecycle hooks, edge cases, and integrations with existing services.

Dependencies are invisible

AI doesn't know which endpoints, schemas, or services are affected by a change until it's too late.

Context gets lost between sessions

Every new session starts from scratch. Patterns, conventions, and past mistakes aren't carried forward.

Exploration burns tokens, not progress

Agents spend half their budget reading your codebase before writing a single line of implementation code.

After

Code-referenced tickets agents can run

Every file, entity, and endpoint mapped

Scope analyzes your codebase and tells your AI exactly what to change, where, and in what order.

Feature-complete from the first run

Structured decomposition ensures nothing is missed — integrations, callbacks, tests, and edge cases included.

Less exploration, more execution

AI agents pull context via MCP and spend tokens writing code instead of discovering architecture.

2 sentences to working implementation

Describe what you want in plain English. Scope handles the decomposition. Your AI builds it.

“We've all been in that sprint planning meeting where someone opens a ticket and... it's a black box. No context. No design. No acceptance criteria.”

Arbisoft Engineering Blog

You're already doing this the hard way

Explaining context to your AI tool, re-reading code, manually breaking down features. Scope does all of that automatically.

Without Scope

You do the work AI should be doing

Writing detailed prompts for AI

Re-explaining your architecture every session

Maintaining CLAUDE.md / rules files

Manual, gets stale, limited context

Reading code to give AI context

You spend 30 min so AI can spend 5 min

Fixing what AI missed

Manually adding integrations and edge cases

Re-running after AI goes off track

Token waste from backtracking and rework

All that effort. Still incomplete features.

With Scope

One flow from intent to execution

Connect your repository

Scope builds a complete model of your codebase in ~2 minutes

Describe the feature in plain English

Two sentences is all it takes

Get a codebase-aware implementation plan

Exact files, entities, dependencies, and acceptance criteria

Gaps caught before coding starts

Missing integrations and edge cases surfaced up front

Your AI tool executes with full context

Claude Code, Cursor, or Codex builds it complete

One workflow. Code-aware tickets every cycle.

What Scope is different from

Scope doesn't replace your coding tools or issue tracker. It makes your AI agent dramatically smarter about your specific codebase.

Capability
Jira/Linear AI
Claude Projects
ChatPRD
Scope
Understands your codebase
Agent-ready implementation tickets
Exact files/functions to change
Gap detection before coding
3-tier
MCP delivery for coding agents
12 tools
Output for existing workflow
issues only
chat output
PRD output
32 fields

Scope is the only tool that gives AI agents deep understanding of your codebase before they write a single line.

From plain English to complete implementation

Scope analyzes your codebase and gives your AI tool everything it needs to build the full feature — not just the obvious parts.

Connect your repo

acme/ecommerce-app

Connected via GitHub

Analyzing codebase...

Codebase understood

Entities extracted14
Endpoints mapped23
Dependencies indexedReady
UserOrderProductPaymentNotification

How it works

From a 2-sentence description to a complete, working implementation.

Connect your repo

Link GitHub and Scope builds a complete model of your entities, endpoints, and dependencies.

~2 min

Describe what you want

Write it in plain English. Scope maps it to your existing code and catches what needs clarification.

2 sentences

Scope decomposes it

Generates a codebase-aware plan: exact files, dependencies, integrations, and edge cases — nothing missed.

Codebase-aware

Your AI builds it

Claude Code, Cursor, or Codex executes with full context. Complete features, not partial implementations.

MCP + Markdown

Why AI tools build more with Scope

Scope gives your AI agent the codebase context it needs to ship complete features, not just starting points.

Deep codebase understanding

Scope parses your entities, relationships, endpoints, and dependencies in ~2 minutes.

Your AI agent starts with full architectural context, not guesses.

Nothing gets missed

Catches missing integrations, lifecycle hooks, and edge cases before your AI starts coding.

The difference between 60% done and 100% done.

Smart decomposition

Breaks features into ordered, dependency-aware steps your AI tool can execute sequentially.

Right order, right scope, right output.

Works with your AI tools

Delivers context via MCP to Claude Code, Cursor, Codex, or any compatible agent.

No workflow changes. Just better results.

0 min

To analyze your codebase

Connect GitHub and Scope builds a complete model

0%

Feature completeness

Every integration, hook, and edge case covered

0 tools

MCP tools for your AI agent

Works with Claude Code, Cursor, and Codex

0 fields

Per generated ticket

Files, entities, dependencies, and acceptance criteria

Who Scope is for

Anyone using AI coding tools who wants complete features, not just a starting point.

Developers using AI tools

Get feature-complete output from Claude Code, Cursor, or Codex. Stop filling in the gaps your AI agent missed.

Founders and solo builders

Describe what you want in 2 sentences. Scope breaks it down. Your AI tool builds the whole thing.

Engineering leads

Standardize how features get decomposed and handed off to AI agents. Less rework, more shipping.

Product managers

Understand your codebase without reading code. Write specs that map to real files and entities.

Built for AI-native delivery

Scope fits your current workflow while giving coding agents structured context to execute faster.

What Scope generates

Implementation tickets

Agent-ready issues with exact files, APIs, and acceptance criteria

MCP context

12 MCP tools for tickets, entities, endpoints, and dependencies

Codebase knowledge

Tree-sitter + semantic indexing over your project structure

Impact context

What changes, what breaks, and what should ship first

+

Where it ships

Claude Code
Cursor
Jira
Linear
Notion
GitHub Issues
Markdown workflows
Any MCP client
Markdown exportTree-sitter parsingQdrant semantic searchMCP delivery

Same feature. Completely different results.

What happens when your AI agent has codebase context vs. when it doesn't.

Before Scope

AI builds the obvious 60%

1

You describe

"Add notifications to checkout"

2

AI explores

Burns tokens reading your codebase to figure out where to start

3

Incomplete output

Builds the core service but misses lifecycle hooks and integrations

4

You fill gaps

Manually add the callbacks, edge cases, and tests AI skipped

5

Result

Hours of back-and-forth for a partial implementation

Partial feature, manual cleanup

After Scope

AI builds the complete feature

1

You describe

"Add notifications to checkout"

2

Scope maps

Finds CheckoutService, identifies missing NotificationService and hooks

3

Gaps caught

Surfaces missing integrations, edge cases, and dependencies

4

You confirm

Answer a few product decisions in minutes

5

AI executes

Builds every service, callback, test, and integration — nothing missed

6

Result

Complete feature with zero manual gap-filling

Feature-complete output, no rework

Same feature request100% of the feature, not 60%
Your Code Stays Yours

We analyze your codebase. We never store your code.

Scope extracts relationships, data models, and context from your repo. Your source code is never retained — only the metadata that powers your specs.

Source code never stored

Scope reads your code during analysis and extracts metadata — data model names, properties, feature paths. The actual source code is processed in memory and discarded.

You control what's shared

API keys are scoped to your projects. You choose which repos to connect. Nothing is shared between users or projects.

Isolated by design

Each project's context is stored in isolated, encrypted storage. Enterprise-grade security practices throughout.

What we store

  • Data model names, properties, and relationships
  • Feature paths and access rules
  • Technology and framework choices
  • Your project requirements and generated specs

What we never store

  • Your source code files
  • Environment variables or secrets
  • Git history or commit contents
  • Any raw file content from your repository

Simple pricing

Start free. Upgrade for premium analysis and higher-throughput planning.

Free

$0

Start building complete features

  • Codebase analysis
  • Implementation-ready ticket generation
  • Core MCP workflow tools
  • 200K signup tokens + monthly token allowance
  • No credit card required

Buy token packs only if you need more volume

Get Started Free
Most Popular

Pro

$20/mo

For teams shipping at scale

  • Everything in Free
  • Premium analyze_codebase tool
  • Advanced impact analysis
  • Premium AI models
  • Priority queue + faster support
  • Roadmap access
Upgrade to Pro

Cancel anytime. Keep your existing Jira/Linear workflow.

Questions? Answers.

No. Scope reads your source code during analysis to extract structure and metadata — data model names, properties, feature paths, relationships, and patterns. The actual source code is processed in memory and discarded. Only the extracted context is stored.