research-flow
Workflow for deep project research with grounded references, parallel exploration, etc.
소스 정보
- 저장소
- griddynamics/rosetta
- 최근 소스 활동
- 2026년 8월 19일 22:06
- 감지된 SKILL.md 언어
- 영어
- 스타
- 360
- 포크
- 80
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- research-flow
- description
- Workflow for deep project research with grounded references, parallel exploration, etc.
<research_flow>
<description_and_purpose>
Orchestrates deep research via meta-prompting: craft an optimized research prompt, then execute it in a dedicated subagent.
</description_and_purpose>
<workflow_phases>
<prerequisites phase="0", applies="ALL">
1. All Rosetta prep steps MUST be FULLY completed
2. USE SKILL `load-project-context`, `orchestration`, `hitl`
3. MUST ALWAYS use todo tasks ledger, ASAP. Phases are sequential. Independent tasks can run in parallel.
4. Orchestrator trusts the system and skills; coordinates sequence, artifacts, state, and approvals only.
5. Workflow state MUST be saved to `agents/TEMP/<FEATURE>/research-flow-state.md` file.
6. If `/goal` is set repeat phases 3-4 until goal is met.
</prerequisites>
<context_load phase="1" subagent="researcher" role="Context gatherer for research scope" subagent_required_model="inherit">
1. Read all lines from CONTEXT.md, ARCHITECTURE.md, and IMPLEMENTATION.md.
2. Input: user research request. Output: loaded project context.
3. Update `research-flow-state.md`.
</context_load>
<prompt_craft phase="2" subagent="researcher" role="Research prompt architect" subagent_required_model="inherit">
1. Create an optimized research prompt for the user request.
2. Save as `research-prompt.md` in FEATURE PLAN folder. Output ONLY the optimized prompt.
3. Input: user request + project context. Output: `research-prompt.md`.
4. Required skills: `reasoning`
5. Update `research-flow-state.md`.
6. HITL approval of research prompt before execution.
</prompt_craft>
<execute_research phase="3" subagent="researcher" role="Deep research executor" subagent_required_model="inherit">
1. Execute the approved research prompt as a separate subagent.
2. Input: approved `research-prompt.md`. Output: `docs/<feature>-research.md`.
3. Required skills: `research`
4. Update `research-flow-state.md`.
</execute_research>
<finalize phase="4" subagent="researcher" role="Research finalizer" subagent_required_model="inherit">
1. Finalize `docs/<feature>-research.md`.
2. Input: completed research document. Output: finalized research document.
3. Update `research-flow-state.md` and mark complete.
</finalize>
</workflow_phases>
</research_flow>
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