Overview

What Repo Prompt is, key value props, Agent Mode, and MCP tools.

In this section

Introduction

Repo Prompt is an AI-powered context IDE. It gives you precise control over what a model sees — so you get the best responses from the most powerful reasoning models.

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Why Context Engineering Matters

Agents waste context before they start thinking. Their context windows fill with tool calls, duplicate file reads, and irrelevant code — leaving little room for actual reasoning. Repo Prompt solves this by structuring context upfront: the model reasons about the problem from the first token instead of spending its thinking budget on figuring out what to read next.

Typical Agent Context

  • ~16% system prompts & tool definitions
  • ~38% wasted on duplicate reads & unrelated code
  • ~16% relevant code (finally)
  • ~14% actual reasoning
  • ~16% missing context the agent never found

Repo Prompt Context

  • File tree for project orientation
  • Codemaps for API surface at a glance
  • Complete relevant file contents
  • Git diffs for change awareness
  • Task description — 100% of reasoning spent solving the problem

Three Ways to Work

IDE Mode
Craft precise prompts with full control over file selection, codemaps, and context.
Agent Mode Pro
Hands off context engineering to your coding agents. The same best practices from IDE Mode — codemaps, slicing, token budgets — managed by agents (Codex, Claude Code, Cursor, Gemini, OpenCode) on your behalf, with built-in workflows.

Built-in MCP Server Pro
Any MCP-compatible tool gets access to Repo Prompt's context tools. Claude Code, Cursor, Codex, Gemini CLI, OpenCode — install with one click.

How Context Builder Works

Context Builder is a three-stage pipeline that gives your agents the right context, every time. Learn more →

1. Explore
A discovery agent navigates your codebase, reading files and understanding relationships.

2. Curate
Relevant files are selected within a token budget, using codemaps and line slices for maximum density.

3. Handoff
A structured prompt with curated context is passed to an analysis model for planning, review, or deep Q&A.

Built-in Workflows

Ready-made context engineering pipelines your agents run directly:

  • Plan & Build (/rp-build) — Discovery → plan → implement in one session
  • Orchestrate (/rp-orchestrate) — Plans, decomposes, dispatches sub-agents across providers
  • Review (/rp-review) — Git diffs + codebase context for grounded code reviews
  • Investigate (/rp-investigate) — Systematic exploration with evidence gathering
  • Refactor (/rp-refactor) — Two-pass: analyze then implement preserving behavior

Agent Orchestration

Repo Prompt is a full control plane for multi-agent workflows via MCP. The agent_run tool provides: start, wait/poll (multi-session), steer, respond, cancel. Any MCP-connected agent can orchestrate complex workflows — not just Repo Prompt's built-in agents.

The /rp-orchestrate workflow automates this: Context Builder generates a plan → decomposes into tasks → dispatches sub-agents in parallel or sequence → verifies each result. Learn more →

Why It Matters

Without Curated Context

  • Misses tradeoffs and edge cases
  • Architectural drift from existing patterns
  • Duplicates functionality that already exists
  • Generic advice disconnected from your codebase

With Curated Context

  • Considers the full picture before acting
  • Follows existing patterns and conventions
  • Finds simpler solutions using what's already there
  • Grounded feedback tied to real code

CLI Providers

Already paying for Claude Pro/Max, ChatGPT Plus/Pro, or Google AI? Use those same models in Repo Prompt with CLI Providers — no additional API costs. These providers power Agent Mode, Chat Mode, and Context Builder workflows. Learn more →

Free vs Pro

Feature Free Pro
Token Limit 32K Unlimited
File Selection & Workspaces ✓ ✓
Own API Keys ✓ ✓
CLI Providers ✓ ✓
Codemaps — ✓
MCP Server — ✓
Context Builder — ✓
Custom API Providers ✓ ✓
Agent Mode & Orchestration — ✓

Who Is Repo Prompt For?

  • Developers, researchers, or anyone working with AI on their files — Repo Prompt gives you precise control over what context AI sees, whether you're writing code, analyzing documents, or exploring data
  • Professionals shipping production-ready code — Context Builder helps plan architecturally sound changes that fit naturally into existing codebases, so AI suggestions don't fight your patterns
  • Teams that care about code quality — the /rp-review workflow provides world-class AI code reviews powered by Context Builder, grounding feedback in your actual codebase rather than generic advice

Get Started

Ready to build better AI prompts? Here's where to go next:

Installation

Repo Prompt is a native macOS application available for direct download from our website.

Onboarding Walkthrough

Ray Fernando put together an excellent end-to-end onboarding video that walks through Repo Prompt from install through your first orchestrated workflow:

Repo Prompt: Why Is Nobody Talking About This? - YouTube

Repo Prompt: Why Is Nobody Talking About This?

Download

Get the latest version directly from Repo Prompt:

Download for macOS

Installation

  1. Download the .dmg file from the link above
  2. Open the downloaded file
  3. Drag Repo Prompt to your Applications folder
  4. Eject the disk image
  5. Open Repo Prompt from Applications or Spotlight

System Requirements

  • macOS 14.0 (Sonoma) or later
  • Apple Silicon (M1/M2/M3) or Intel Mac
  • ~50MB disk space

First Launch

  1. Open Repo Prompt from Applications or Spotlight
  2. Grant folder access when prompted (required to read your code)
  3. Open a workspace: File → Open or drag a folder onto the app

Tip: You can open Repo Prompt from Terminal with open -a "Repo Prompt" /path/to/folder or use the URL scheme repoprompt://open?path=/path/to/folder

Updates

Repo Prompt checks for updates automatically. When an update is available, you'll see a notification in the app. You can also manually check via Settings → License & Updates.

Platform Availability

Repo Prompt is built natively with Swift and SwiftUI, which means it's currently macOS-only. Multi-platform support is planned but not yet available.