griddynamics/rosetta
Enforce organizational standards across every AI coding agent
What it solves
AI coding agents often struggle in professional team environments because they lack project-specific context, ignore architectural constraints, and skip critical engineering discipline. Without structured guidance, agents tend to guess based on limited file context, ignore security/compliance guardrails, and jump straight into coding without planning or validation, leading to errors that require expensive rework.
How it works
Rosetta layers instructions at runtime across three levels: Core (best practices), Organization (standards and policies), and Project (architecture and constraints). It uses an orchestration layer to adapt these instructions to your specific AI tool (like Claude Code, Cursor, or Copilot). The system follows a structured workflow—Prepare → Research → Plan → Act → Validate—incorporating human-in-the-loop approval gates and using separate subagents for fresh-context reviews and execution-backed validation.
Who it’s for
- Individual Builders seeking deep project context and ready-made coding/testing flows without complex prompt scaffolding.
- Organizations needing a single, versioned source of truth for engineering standards that works across different AI tools and models without vendor lock-in.
Highlights
- Layered Context: Automatically builds a workspace baseline including tech stack, architecture, and dependencies.
- Tool Agnostic: Works with existing IDEs via plugins or MCP-compatible agents.
- Workflow Enforcement: Implements structured SDLC activities with explicit approval gates.
- Safety & Governance: Provides guardrails to prevent dangerous actions and ensure sensitive data is handled correctly.
- Git-Integrated: All instructions are authored in Markdown and versioned in Git for team-wide reuse and control.