Research-question shaping
Turn raw ideas, notes, or scattered materials into candidate research spines and feasible paper directions.
Open workflow suite
Research Architect
AI research workflow skill suite for turning ideas into manuscripts.
Research Architect helps move from a rough topic to a defensible paper path: question candidates, literature mapping, study design, evidence registers, draft construction, and manuscript audit.
Research planningLiterature mappingEvidence traceabilityManuscript audit
Paper workflow
Traceable1
Idea intake
Collect context, constraints, target venue, and available materials.
2
Research spine
Select the strongest question, claim path, and contribution shape.
3
Study design
Translate the spine into experiments, analysis, or validation work.
4
Evidence bank
Organize results, citations, claims, and figure candidates.
5
Draft audit
Check draft logic, source support, and manuscript risks before submission.
Designed to make the GitHub workflow easy to discover, inspect, and reuse.
From topic to draft
What is the Research Architect AI research workflow?
Research Architect is an AI-assisted research workflow skill suite that helps researchers benchmark strong papers, reverse-engineer research structure, design experiments, organize evidence, and build a manuscript-ready research spine. It is designed for the messy middle between a promising idea and a paper draft: the point where the question, method, evidence, claims, and figures must start reinforcing one another.
Evidence-first drafting
Build claims, figures, citations, and manuscript sections from traceable source material instead of loose prose.
Manuscript readiness checks
Audit drafts for spine clarity, evidence traceability, citation integrity, copying risk, and overclaiming.
How does Research Architect turn ideas into manuscripts?
The workflow starts by separating a broad topic from a testable research spine. Instead of asking for a finished paper too early, it helps define the research question, the strongest contribution angle, the evidence needed, and the study design that can support the claim.
After the spine is clear, the workflow organizes literature, evidence, citations, and figure candidates around that structure. The draft step then has a concrete job: transfer the spine into manuscript sections while preserving claim-level support and revision rationale.
- 1Idea intake: capture topic, constraints, venue expectations, and available research materials.
- 2Research spine: define the claim path, research gap, contribution, and expected evidence.
- 3Study design: convert the spine into an experiment, analysis, benchmark, or validation plan.
- 4Evidence bank: map results, claims, figures, and citations before drafting.
- 5Draft audit: check source support, overclaiming, copying risk, and manuscript coherence.
What can researchers use Research Architect for?
- Benchmark strong papers in a target area and identify what makes their research structure work.
- Reverse-engineer problem framing, contribution logic, experiment design, evidence flow, and manuscript shape.
- Plan experiments or analyses that map directly back to the research spine instead of drifting into disconnected tasks.
- Organize evidence, citations, claims, and figure candidates before writing the full draft.
- Audit whether a manuscript is supported by the evidence it cites and clear enough to revise toward submission.
Related ScaleMindLabs reading
Agents & Orchestration
Engineering patterns for tool use, workflow control, and multi-step agent systems.
Read moreEvaluation & Observability
Methods for checking AI outputs, traceability, calibration, and quality drift.
Read moreRAG retrieval quality
Why retrieval systems can find the right source but still assemble the wrong answer.
Read more