By griddynamics
Orchestrate AI agent workflows across IDEs with structured planning, implementation, testing, and documentation generation, plus infrastructure-as-code support and multi-agent coordination.
Rosetta ad-hoc adaptive meta-workflow that constructs, tracks, reviews, and executes a tailored execution plan per user request using building blocks and available instructions. Useful for small or simple tasks if none other workflows matches. Lightweight.
Rosetta coding and implementation workflow, includes discovery, tech specs, tech plan, subagent plan review, user plan review, implementation, subagent review implementation, validation, user review, and final validation with reviewer gates, HITL gates, and subagent delegation.
Phase 1 of init-workspace-flow, contains detect workspace mode, composite status, and existing file inventory.
Phase 3 of init-workspace-flow, contains analyze tech stack and produce TECHSTACK, CODEMAP, DEPENDENCIES files.
Phase 6 of init-workspace-flow, contains create CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, ASSUMPTIONS.md, AGENT MEMORY.md.
Rosetta Full subagent. Transform requirements into clear, testable tech specifications and architecture.
Rosetta Lightweight subagent. Gather project context, existing patterns, affected areas, and dependencies.
Rosetta Full subagent. Execute implementation and testing tasks with high quality, assuming engineering identity provided by orchestrator.
Rosetta Lightweight subagent. Run simple commands, collect results, and summarize to prevent parent context overflow.
Rosetta Full subagent. Execution planning from approved intent/specs, producing sequenced plans scaled to request size.
Rosetta skill to create CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, ASSUMPTIONS.md, and AGENT MEMORY.md from workspace analysis.
Rosetta skill to extract recurring coding and architectural patterns from workspace code into reusable templates.
Rosetta skill to create local cached agent rules configured for IDE/OS/project context.
Rosetta skill to generate IDE/CodingAgent shell files from KB schemas.
Rosetta skill to verify workspace initialization completeness and run catch-up for missed artifacts.
External network access
Connects to servers outside your machine
Uses power tools
Uses Bash, Write, or Edit tools
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Rosetta is a meta-prompting, context engineering, and centralized knowledge management for AI coding agents. It provides structured context - rules, skills, workflows, and sub-agents - guiding AI systems to operate with a deep understanding of system architecture, domain constraints, and engineering standards. Rosetta also accelerates project onboarding by reverse-engineering architecture and domain context, improving the reliability and consistency of AI-generated code.
Every AI interaction follows four phases: Prepare (load guardrails and context), Research (search the knowledge base), Plan (produce a reviewable plan), Act (execute with full context). Read more in the Usage Guide.
Your IDE connects to the Rosetta MCP server. The server exposes guardrails and common best practices, and provides a menu of available instructions — workflows and coding conventions. The coding agent selects only what it needs for the current task; Rosetta delivers just those, keeping the agent's context lean. By design, no source code or project data reaches Rosetta.
Rosetta is designed to not see your source code. It only serves knowledge and instructions to the agent. The agent loads only what it needs per request (progressive disclosure) and follows your organization's workflows.
npx claudepluginhub griddynamics/rosetta --plugin rosettaHarness for Claude Code — skills, /harness:* slash commands, persona subagents, lifecycle hooks, and MCP tools without per-repo `harness setup`. Sibling plugins exist for Cursor, Gemini CLI, and Codex.
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