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.
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:
- Plan — break the question into 3–6 sub-questions.
- Gather — for each sub-question, query the agent’s retrieval/search tools (several calls per round).
- Reflect — assess what’s answered vs missing or contradictory; turn gaps into new sub-questions.
- Iterate — keep going until coverage is good or the budget runs out; stop early when a round adds nothing new.
- 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.
Deep Research uses whatever retrieval tools the host agent has — that’s the whole point.
| The agent has… | What Deep Research does |
|---|
| A web search tool (Bing, Brave, Google) and a knowledge base | Plans sub-questions and queries both per sub-question, cross-checks, iterates |
| A knowledge base only | Iterative RAG with query reformulation each round |
| A web search MCP only | Iterative web search, always citing sources |
| No retrieval tool at all | Falls back to multi-pass reasoning + self-critique, and explicitly flags “no external sources” — it will not invent sources |
Add it to an agent
- Open the agent in Agent Creator → Capabilities → Add Capability.
- Add Deep Research (category Research). It appears as a tool the agent can call.
- (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.
- 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.
Budget
The research sub-run has its own budget, independent of the main conversation, configurable on the
capability:
| Setting | Default | What it caps |
|---|
max_turns | 6 | Maximum rounds/turns inside the research sub-loop |
token_budget | 60000 | Token ceiling for the whole sub-run |
tool_call_budget | 20 | Maximum tool calls during the research |
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.
Output
The report is rendered in the conversation (and the canvas for substantial reports), structured as:
## Executive summary
## Findings (per sub-question, with inline [source, date] citations)
## Open questions
## Sources (deduplicated list)
