rosetta

<div align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/web/assets/brand/rosetta-logo-full-color-white-text.png"> <img src="docs/web/assets/brand/rosetta-logo-full-color-black-text.png" alt="Rosetta" width="200"> </picture> <p><strong>Engineering governance and context for AI coding agents — shared instructions, architecture, standards, workflows, and guardrails in every session.</strong></p> <p> <a href="https://pypi.org/project/rosetta-mcp/"><img src="https://img.shields.io/pypi/v/rosetta-mcp.svg" alt="MCP"></a> <a href="https://pypi.org/project/rosetta-mcp/"><img src="https://img.shields.io/pypi/dm/rosetta-mcp.svg" alt="Downloads"></a> <a href="https://pypi.org/project/rosetta-cli/"><img src="https://img.shields.io/pypi/v/rosetta-cli.svg" alt="CLI"></a> <a href="https://pypi.org/project/rosetta-cli/"><img src="https://img.shields.io/pypi/dm/rosetta-cli.svg" alt="Downloads"></a> <a href="https://github.com/griddynamics/rosetta/actions/workflows/publish-rosetta-mcp.yml"><img src="https://github.com/griddynamics/rosetta/actions/workflows/publish-rosetta-mcp.yml/badge.svg" alt="Rosetta MCP"></a> <a href="https://github.com/griddynamics/rosetta/actions/workflows/publish-rosetta-cli.yml"><img src="https://github.com/griddynamics/rosetta/actions/workflows/publish-rosetta-cli.yml/badge.svg" alt="Rosetta CLI"></a> <a href="https://github.com/griddynamics/rosetta/actions/workflows/publish-instructions.yml"><img src="https://github.com/griddynamics/rosetta/actions/workflows/publish-instructions.yml/badge.svg" alt="Instructions"></a> <a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.12+-blue.svg" alt="Python 3.12+"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-Apache--2.0-blue.svg" alt="License: Apache-2.0"></a> </p> </div>

What is Rosetta

https://github.com/user-attachments/assets/6df6e217-3e5c-4691-84ed-7440701a87de

AI coding agents are great — until you try to use them across a real team. Everyone builds their own prompts and instructions, knowledge stays in silos, and the agent — not knowing your architecture or constraints — guesses from a few open files and confidently does the wrong thing.

That's why we built Rosetta — open-source engineering governance and context for AI coding agents. It's not another proprietary agent; it works with the tools you already use (Claude Code, Cursor, Copilot, Codex, and other MCP-compatible agents) and loads your team's shared engineering instructions into every session. Everything is versioned in Git and can run inside your perimeter.

Teach agents how to think, not what to do. The model already knows Python and React; what it lacks is your engineering discipline. That's what Rosetta encodes.

Rosetta-guided work follows five phases — Prepare → Research → Plan → Act → Validate — with approval gates at the key decision points. Read more in the Usage Guide.

[!NOTE] If you are effectively using your current setup, writing your own skills, and managing AI using your own processes, you probably don't need Rosetta.

Top Workflows

1. coding-flow: AI creates features, fixes defects, and performs refactoring, everything end-to-end. AI performs discovery, design, specs and a plan, user review, then AI implements and runs separate review and validation passes (including running application). Most useful for medium to large coding tasks, and for controlled component-by-component migration/modernization work.
2. requirements-authoring-flow: AI works with user and raw artifacts to define entire-application requirements. AI discovers context and existing constraints, captures intent, drafts atomic requirement units, validates them, and finalizes traceability artifacts. This is the most efficient use of coding agents. Requirements then Coding.
3. security-flow: AI runs an auth