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Deep Research is a capability you add to any agent. When the agent calls it, it runs a bounded, multi-round investigation — plan → gather → reflect → iterate → synthesize — over that agent’s own retrieval tools (a knowledge base, Bing/Brave/Google search, any search MCP) and returns a structured, cited report. It’s the difference between a single quick lookup and a thorough, sourced answer.
Deep Research is a system tool (like Memory) — drop it onto an agent from the capability catalog and it immediately operates over whatever tools that agent already has. It does not bring its own data source; it orchestrates the agent’s.

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What it does

A normal turn does one pass: the model may call a tool once and answer. Deep Research instead runs a short sub-loop, dedicated to one research question, with its own budget:
  1. Plan — break the question into 3–6 sub-questions.
  2. Gather — for each sub-question, query the agent’s retrieval/search tools (several calls per round).
  3. Reflect — assess what’s answered vs missing or contradictory; turn gaps into new sub-questions.
  4. Iterate — keep going until coverage is good or the budget runs out; stop early when a round adds nothing new.
  5. Synthesize — return a structured report: Executive summary · Findings (with inline citations) · Open questions · Sources.
The report flags any claim not backed by a cited source, and never fabricates data or sources.

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It adapts to the agent’s tools

Deep Research uses whatever retrieval tools the host agent has — that’s the whole point. It is read-only: it never calls write/create/update/send actions, and it cannot call itself (recursion-safe).

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Add it to an agent

  1. Open the agent in Agent Creator → Capabilities → Add Capability.
  2. Add Deep Research (category Research). It appears as a tool the agent can call.
  3. (Recommended) also add the Deep Research skill — it tells the agent when to use deep research and how to present the report. Pure guidance; no extra setup.
  4. Make sure the agent has at least one retrieval tool (a knowledge base or a web search MCP) so the research can cite real sources. Without one, Deep Research still runs but answers from reasoning only, marked unverified.
Deep Research uses the agent’s own model for its sub-loop. If the agent’s model is invalid or its max_tokens is very low, Deep Research will fail like any other turn — check the agent’s model settings first.

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Budget

The research sub-run has its own budget, independent of the main conversation, configurable on the capability: Higher budgets = deeper, more thorough (and slower, costlier) research. These are server-side; the model cannot raise them itself.

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When to use it — and when not to

Use Deep Research for: open-ended or comprehensive questions that need several searches and synthesis — “comprehensive analysis of X”, “everything about Y”, “investigate Z thoroughly”, state-of-the-art reviews, competitive landscapes. Don’t use it for: a single quick fact or a one-shot lookup — a normal turn (or one direct tool call) is faster and cheaper. The Deep Research skill already instructs the agent to skip it for quick questions.

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Output

The report is rendered in the conversation (and the canvas for substantial reports), structured as:
Because it can take several rounds, expect Deep Research to be noticeably slower than a normal reply — it’s doing many searches and a synthesis pass, not a single answer.