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Skill

/research-flow

Workflow for deep project research with grounded references, parallel exploration, etc.

From plugin
rosetta
330200 skills24 agents63 commands
Install
$ npx -y skills add griddynamics/rosetta --skill research-flow --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/research-flow

Context preview

The summary Claude sees to decide when to auto-load this skill.

Workflow for deep project research with grounded references, parallel exploration, etc.

SKILL.md

research-flow.SKILL.md
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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