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OpenAI documents both model-managed agentic search and a separate deep-research approach; Anthropic describes progressive searches that use earlier results to shape later queries. These are different workflows, not guarantees of accuracy. The right choice depends on whether the task needs a quick fact, iterative investigation, or a structured report.
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What multi-pass search means
A multi-pass chat agent follows a deliberate loop: retrieve relevant sources, inspect what they establish, identify unanswered material questions, and search again only when a concrete gap remains. It then writes an answer with citations connected to the claims those sources support.
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- Inspect: Determine which parts of the question the results answer and whether the sources are sufficient for those claims.
- Find a reason to continue: Note a specific unanswered question, source conflict, or evidence weakness.
- Search again: Use a narrower or refined query aimed at that issue.
- Answer with evidence: Attach citations to the relevant claims and avoid stating more than the sources support.
This is a design pattern, not a universal provider feature. OpenAI describes agentic search as a model reasoning about results and deciding whether to continue; Anthropic explicitly describes progressive searches informed by earlier results. Neither description establishes that repeated searching by itself makes answers accurate.
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Choose the search workflow for the job
OpenAI distinguishes non-reasoning web search, agentic search with reasoning, and deep research. Its documentation frames agentic search as useful for complex workflows where the model can analyze results and decide whether to search further. Deep research is intended for multi-step or in-depth questions that combine multiple sources; ordinary search is faster for quick facts. Availability of Deep Research varies by plan and country or territory. See OpenAI’s web-search API documentation and OpenAI’s Deep Research guidance.
Anthropic describes progressive searching in its Claude web-search interface: earlier results can inform subsequent queries, helping with light research and more comprehensive answers. Its API documentation also covers query refinement, domain controls, and citation data. See Anthropic’s web-search documentation.
Use a short lookup for a bounded fact; use model-managed or progressive searches when the answer depends on resolving specific gaps; reserve an extended research workflow for questions that require combining sources into a structured report. These are workflow distinctions, not a neutral ranking of providers. The official documentation cited here does not establish comparative accuracy, latency, or cost.
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Decide when an agent should search again
A follow-up search is warranted when it has a defined purpose. For example, the first results may omit a material part of the question, leave a time-sensitive detail unverified, present conflicting accounts, or rely on a source that does not directly support the intended claim.
- Unanswered material question: Refine the query to retrieve evidence for the missing point.
- Conflict between sources: Search for a more authoritative or directly relevant source that can clarify the disagreement.
- Insufficient support: Seek evidence that directly substantiates the claim rather than repeating a broad query.
If the results already answer the question adequately, stop. Repeating broad searches without a specific gap can add noise rather than useful evidence. Keep the decision rule separate from the provider’s tool controls: a setting that permits multiple calls does not itself determine when another call is justified.
How to build an agent that answers with citations
Select the integration surface and search controls
OpenAI’s Responses API supports web search for up-to-date information with sourced citations. Its Agents API documentation describes live, cached, and disabled search modes, along with optional context-size and domain settings. Anthropic’s Claude Messages API documents web search and progressive querying, as well as domain allow/block controls and localization settings. Consult the current Responses API documentation, OpenAI Agents API documentation, and Claude web-search documentation for the available settings.
When choosing among these integration surfaces, check whether search is always enabled or selected by the model, whether access is live or cached, how many calls are allowed, whether domains can be restricted, whether localization is configurable, and what citation metadata is returned. Match those controls to the task and deployment; the documentation does not support a general performance winner.
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OpenAI’s Responses API documentation describes URL citation annotations that include a URL, title, and location. Anthropic’s web-search responses can include a source URL, title, and cited text. These fields let an application present citations near the claims they support instead of returning a detached list of links.
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Make citation behavior part of answer generation: each material factual claim should be supported by the evidence cited beside it. A link that merely appears at the end of an answer is weaker if readers cannot tell which statement it substantiates. A citation also does not validate claims beyond the source’s actual scope.
Using supplied search results
If your application supplies search results to the model rather than asking the model to retrieve them, Anthropic documents a supplied-result format that can include a source identifier and title, with citations enabled so the response can cite those results. See Anthropic’s citation documentation. Preserve the result identifiers and source details through the answer-generation step so citations can be tied back to the provided evidence.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the documentation does—and does not—establish
The official documentation describes available search and citation capabilities, not a neutral head-to-head evaluation. It provides no substantiated comparison here for accuracy, latency, cost, or citation quality. An agent’s workflow should therefore be selected for its required controls and output—not on an unsupported assumption that one provider or more search passes will produce better answers.
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API behavior and product availability can change. Check the linked official documentation for current version-specific details before implementing a deployment.
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