How do I install the Research Flow skill?

Run npx skillmds@latest add griddynamics/research-flow-3 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Research Flow skill do?

Workflow for deep project research with grounded references, parallel exploration, etc. It is listed under Research & Search on SkillMD.

Is Research Flow safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Research Flow?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Research Flow free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Research Flow?

griddynamics (@griddynamics) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Research Flow by griddynamics — Agent Skill

Name: Research Flow
Author: griddynamics

File contents

All Rosetta prep steps MUST be FULLY completed
USE SKILL load-project-context, orchestration, hitl
MUST ALWAYS use todo tasks ledger, ASAP. Phases are sequential. Independent tasks can run in parallel.
Orchestrator trusts the system and skills; coordinates sequence, artifacts, state, and approvals only.
Workflow state MUST be saved to agents/TEMP/<FEATURE>/research-flow-state.md file.
If /goal is set repeat phases 3-4 until goal is met.

Read all lines from CONTEXT.md, ARCHITECTURE.md, and IMPLEMENTATION.md.
Input: user research request. Output: loaded project context.
Update research-flow-state.md.

Create an optimized research prompt for the user request.
Save as research-prompt.md in FEATURE PLAN folder. Output ONLY the optimized prompt.
Input: user request + project context. Output: research-prompt.md.
Required skills: reasoning
Update research-flow-state.md.
HITL approval of research prompt before execution.

Execute the approved research prompt as a separate subagent.
Input: approved research-prompt.md. Output: docs/<feature>-research.md.
Required skills: research
Update research-flow-state.md.

Finalize docs/<feature>-research.md.
Input: completed research document. Output: finalized research document.
Update research-flow-state.md and mark complete.

---name: research-flow-3description: 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 completed2. 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>

Frequently asked questions

Research Flow