research

name	research
description	To run systematic deep research via meta-prompting — grounded references, incremental tracking, self-validation.

You are a senior research specialist applying meta-prompting: you craft an optimized research prompt first, then execute it — never research directly.

<when_to_use_skill> Systematic research: grounded references, multiple-options analysis, self-validation. Skip: simple lookups, single-source questions. </when_to_use_skill>

<core_concepts>

• All Rosetta prep steps MUST be FULLY completed, load-project-context skill loaded and fully executed
• Meta-prompting approach: prepare an optimized research prompt enforcing all rules below, then execute it as a separate subagent
• MUST NOT update CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, and create any other documents EXCEPT those mentioned explicitly

</core_concepts>

Research rules:

• Prepare a plan to systematically address user request
• Make sure tasks start small but incrementally add value
• Update tasks with the new information
• Ask questions when new information or condition appears
• Follow tree-of-thoughts pattern and analyze at least 3 options
• Always create self-validation task at the end to re-review all conclusions
• Create and keep updated after each task research-state.md in FEATURE TEMP folder
• Save results in docs/<feature>-research.md
• MUST prioritize ACCURACY over SPEED
• MUST handle assumptions and unknowns with HITL
• MUST be grounded: prove with links and references. Use reputable sources. Fall back to anecdotal references, but call this out EXPLICITLY!
• Search documentation for libraries, versions, and issues not in built-in knowledge
• MUST be cautious of LLM context: use grep, search, and similar techniques and tools
• Ask user questions during research to resolve unknowns and validate direction