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Research Agent is the engine that powers searches in Consensus. Instead of running one search at a time, it reasons across multiple tools, chains them together, and returns citation-backed answers grounded in peer-reviewed research. You don’t switch it on. Every Pro message and Deep Review runs through Research Agent.

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What it does

  • Plans multi-step searches. Breaks a complex question into sub-questions and runs targeted sub-searches when a single query isn’t enough.
  • Applies filters in plain language. Stack recency, journal quartile, citation count, sample size, study type, and population by describing what you want. Research Agent picks the right filters automatically.
  • Traces authors and citations. Give it a DOI, a paper title, or an author name to explore co-authors, influential papers, and how the work developed over time.
  • Excludes what you don’t want. Filter out the wrong population, methodology, publication type, or author.
  • Carries context between searches. Follow-up questions build on the previous search, so you can refine, pivot, and synthesize without starting over.
  • Reads and compares papers. Reads full text where available, surfaces relevant findings, and builds comparison tables across studies.
  • Finds gaps. Detects missing populations or research areas in a Library collection or set of papers.

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Effort levels

You choose how much work Research Agent does with the Deep toggle in the search bar. Every level searches the same 400M+ papers; higher levels run more searches and read more papers before answering.

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How to use it

1

Open Consensus

Go to consensus.app.
2

Ask your question

Type a question, topic, messy prompt, or Boolean-style query in the search bar. Research Agent handles all three.
3

Send the message

By default the message runs as a Pro message. Click Deep to upgrade it to a Deep Review for a longer, more comprehensive analysis.
4

Follow up

Ask a follow-up in the same thread. Research Agent keeps the context, so “now only Q1 journals” or “exclude animal studies” just works.
A Research Agent trace showing two parallel searches with year and journal filters, and retrieved, eligible, and included counts

Every answer opens with the agent's trace: papers retrieved, eligible, and included, plus each sub-search and its filters.

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Example prompts

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What you get back

A citation card over a Consensus answer, with the Full Text used badge and the supporting quote highlighted

Hover a citation to see its card. Full Text used means the paper's full text was analyzed.

Answers appear in the thread with in-line citations that link directly to the papers supporting each statement. A document icon with a tick next to a citation means the full text of the paper was used in the analysis; no icon means the abstract was used. Depending on the question, the answer may include:
  • Consensus Meter — a “yes or no” visualization showing where the research leans.
  • Claims & Evidence table — strength of support, reasoning, and key papers for each claim.
  • Research Gaps heat map — areas with limited research.
  • Results timeline and a TL;DR header.
Export any answer with Copy text, Copy with citations (APA, MLA, Chicago, Harvard, LaTeX, AMA/Numeric), or Export as PDF. The papers themselves export as CSV, RIS, or a formatted bibliography from the References panel.
The export menu on the References panel with CSV, RIS, and Bibliography options

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Availability

Research Agent runs in both Pro and Deep modes.
You can also run Research Agent from your AI assistant or code. The MCP server and API run it as a Thread, alongside the underlying paper search.

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Under the hood

Research Agent is a multi-agent system. A planning agent breaks down your question and decides which actions to take; a search agent combs the paper index, your private Library, and the citation graph; a reading agent interprets papers individually or in batches; and an analysis agent synthesizes the results and composes the answer. If no relevant studies meet its quality threshold, it says so rather than inventing an answer.
Research Agent replaced Scholar Agent in May 2026. If you see “Scholar Agent” in older material, it refers to the previous version of this feature.

Deep Review

The longer, more robust version of a search: 50 to 100 papers.

Check a claim against the paper

See the exact quote behind every citation.