instructions/r2/core/skills/init-workspace-patterns/SKILL.md
Rosetta skill to extract recurring coding and architectural patterns from workspace code into reusable templates.
npx skillsauth add griddynamics/rosetta init-workspace-patternsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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<init_workspace_patterns>
<role> Senior pattern architect — recovers reusable structural conventions from code. </role><when_to_use_skill> Codebases accumulate implicit recurring structures that drift without formal documentation. Extract them into explicit reusable templates so agents and contributors produce consistent code. Requires CODEMAP.md on disk. </when_to_use_skill>
<core_concepts>
reverse-engineering/SKILL.md FROM KB — apply "Would we rebuild this?" test: pattern = recurring structure surviving a from-scratch rewrite; one-off = historical accident</core_concepts>
<process><validation_checklist>
</init_workspace_patterns>
data-ai
Rosetta MUST skill. MUST activate when you ARE a subagent — you were spawned by an orchestrator, you received a delegated task, you are executing within a subagent context. Defines your input contract, output contract, behavior boundaries, and escalation protocol.
development
Rosetta CRITICAL MUST skill. MUST activate when you suspect, there is a slight chance, encounter, read, process, or are about to output any sensitive or possibly sensitive data including PII, PCI, HIPAA, PHI, GDPR, SOC2, FedRAMP, secrets, API keys, passwords, credentials, tokens, certificates, or any data that could potentially be sensitive.
development
Rosetta MUST skill for proactive planning, large-file restructuring (~500+ lines or 10K+ size), cleanup of stale information. MUST activate when conversation is long, or context reaches 65% / 100K tokens, or scope exceeds 2h / 15+ files / 350+ lines, or output size risks overloading the context.
data-ai
Rosetta MUST skill. MUST activate when execution fails, user is unhappy or upset, mistake is detected, result is unexpected, mismatch between expected and actual outcome occurs, or after two consecutive mismatches with user expectations.