AI agents can access the web through search, direct APIs, and browser automation; Markdown and structured extraction help turn retrieved pages into useful input. Choose the simplest route that exposes the information or action the agent needs: search to discover sources, an API for a supported operation, and a browser when the required content or interaction exists in a rendered page.
What each kind of web access does
These approaches solve different parts of a web task. Search helps locate relevant pages. An API exposes data or operations in a machine-facing form. Browser automation lets an agent inspect and interact with a website as it is rendered. Markdown and structured extraction are ways to represent retrieved content; they are not substitutes for discovery or interaction.
| Approach | Best suited to | What it does not guarantee |
|---|---|---|
| Search | Finding relevant information or pages for a question or task. | A search result is not necessarily the full page state, and it does not itself perform an action on the destination site. |
| Direct API | Retrieving data or performing a specific operation when the service offers a suitable API. | Coverage depends on the service and task; an API may not expose the needed data or action. |
| Browser automation | Working with rendered pages, visual state, JavaScript-dependent content, or multi-step interactions. | It requires a browser runtime and interaction logic, which may be unnecessary if a simpler request or API is enough. |
| Markdown or structured extraction | Giving a model readable page text, selected fields, links, or elements. | Extraction represents content already reached; it does not, by itself, find pages or reliably operate controls. |
OpenAI’s API documentation describes web search as a way for an agent to look up information to answer a question or complete a task. It documents live search as the default mode, as well as cached and disabled modes, and controls such as context size and allowed domains. Those settings affect how search is used; they do not turn search results into a complete, authoritative record of a site.
Choose the interface by the task
Start with the required outcome, not with a favorite tool. Ask whether the agent needs to discover information, retrieve a known resource, inspect rendered state, or change something on a site. Then use the least complex interface that can actually complete that task.
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Use search for discovery
Search is a good first step when the agent does not yet know which page contains the answer, needs to find relevant sources, or must locate a page before reading it. OpenAI documents live search as the default, alongside cached search and disabled search; the appropriate mode depends on whether the task calls for current lookup or another configured behavior. Use allowed-domain controls when the task should be restricted to particular sites.
After finding a candidate page, the agent may still need to fetch or open it. A snippet or result list can omit context, qualifications, and details present on the destination page. For consequential answers, have the agent inspect the underlying source rather than treating a search summary as the full evidence.
Use an API when it exposes the needed data or action
If a service has an API that covers the exact operation, a direct API call is often a better fit than recreating the same operation through a webpage. APIs typically make the inputs and returned data explicit, which can reduce the amount of page state the agent must interpret. But the existence of an API somewhere does not mean it covers every action or data source relevant to a task.
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The 2024 paper “Beyond Browsing: API-Based Web Agents,” by Yueqi Song, Frank Xu, Shuyan Zhou, and Graham Neubig, reports experiments on WebArena in which hybrid agents combining API use and browsing outperformed browsing-only agents nearly uniformly across the tested tasks. Its reported hybrid success rate was 35.8%, more than 20.0 percentage points above browsing alone. These are results from that paper’s WebArena experiments, not a general success rate for deployed agents or a guarantee that APIs will help on every website.
Use a browser when the page itself matters
Browser automation fits tasks where the agent must see rendered content, work with client-side JavaScript, inspect visual state, or interact through controls. Cloudflare’s Agents browser guide documents browser sessions controlled through the Chrome DevTools Protocol (CDP), including navigation, JavaScript evaluation, DOM reading, screenshots, and network or console inspection.
A browser is not automatically required just because a task concerns a website. If a normal request or direct API supplies the needed information, launching and coordinating a browser can add work without adding value. Reserve browser interaction for state or actions that simpler interfaces cannot provide.
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Use Markdown or structured extraction after reaching a page
Markdown can give a model a readable representation of page text without requiring it to reason over the full visual interface. It is useful when the task is to answer questions from prose or summarize a page. It is still an extraction step: the agent first needs a way to find or reach the page.
When the task calls for specific fields, links, or elements, use a representation suited to that output rather than relying on prose alone. Cloudflare’s browser guide documents separate tools named browser_markdown, browser_extract, browser_links, and browser_scrape, as well as the interactive browser_execute tool. The distinction is practical: use Markdown for readable text, structured extraction for data fields, link listing for URLs, selector-based scraping for chosen page elements, and browser execution for interaction.
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A practical decision path
- Define the output. Is the agent answering a question, collecting specific fields, or completing an action such as submitting a form?
- Check for a suitable API. If the required data or operation is explicitly exposed through an API, use it rather than reproducing the task through the UI.
- Discover what is unknown. Use search to locate relevant pages or sources. Treat results as leads, not as a substitute for checking the destination when its full context matters.
- Choose the representation. Pass page prose as Markdown when the model needs to read it; extract fields, links, or selected elements when the output is structured.
- Escalate to a browser only when needed. If the necessary content appears only after client-side rendering, or the task depends on visible state or interaction, automate a browser.
- Combine interfaces when useful. An agent can use search to find a page, an API for supported data or actions, and a browser for a remaining UI-only step. The WebArena result supports considering hybrid designs in its tested setting, not applying them indiscriminately.
Browser automation: what the agent needs to inspect
A browser agent should gather only the state needed to decide its next action. Depending on the task, that may be the rendered DOM, a screenshot, page text, network activity, or console output. Cloudflare documents these capabilities in its CDP-controlled browser sessions. A visual check can help when layout or visible state matters; DOM inspection can be more direct when the task concerns page structure or text.
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Keep the interaction plan grounded in observable results: navigate, inspect the page, act on a control, and verify the resulting state before assuming success. The need for that verification follows from the core limitation of interaction automation: issuing an action is not the same as confirming the site completed it. Avoid using a browser session for a task that only requires a known API response or a page’s text.
For page reading, prefer a clean text or structured representation over sending a large, irrelevant page state to the model. For interaction, inspect again after an action if the next step depends on the result. This keeps the agent’s context focused while allowing it to detect changed pages or failed transitions.
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Reliability, scope, and cost trade-offs
Reliability depends on whether the selected interface exposes the relevant state and whether the agent verifies the result. Search can locate a page without proving that the page contains the complete answer. An API can be direct and machine-readable but may not cover the task. A browser can reach rendered and interactive state, but it introduces a runtime and additional interaction logic. Markdown improves the form of page content for a model; it cannot restore information that was not retrieved or extracted.
There is no single architecture that is best for every site. The cited WebArena finding is evidence for hybrid approaches in a particular benchmark, while the tool capabilities described by OpenAI and Cloudflare help explain why search, APIs, extraction, and browsers can complement one another. The practical cost question is whether each added layer gives the agent access to something it otherwise lacks. Avoid paying the complexity of a browser when a suitable direct request suffices, and avoid forcing a lightweight fetch onto a task that depends on interactive rendered state.
Troubleshooting common agent failures
- Search results do not answer the question. Open the underlying source or search for a more specific page. A result is for discovery, not necessarily a complete account of page content.
- The page text is empty or incomplete. The content may depend on JavaScript or may not be present in the extracted representation. Inspect the rendered page with a browser, or use a suitable API if one exposes the needed data.
- Markdown is readable but the answer lacks required fields. Use structured extraction or selector-based scraping for specific values, and link listing when the task is to collect URLs.
- A browser action appears to do nothing. Inspect the page and resulting state before continuing. If the needed operation is available through a suitable API, consider using it instead of relying on the UI interaction.
- The agent has too much irrelevant context. Narrow the search scope, extract only the relevant fields or elements, or use page Markdown rather than passing unnecessary interface state.
- A hybrid workflow becomes harder to maintain than the task warrants. Remove interfaces that are not contributing necessary information or actions. The benchmark finding does not mean every task benefits from combining tools.
FAQ
Does Markdown give an AI agent access to the web?
No. Markdown is a readable representation of retrieved page content. The agent still needs search, a direct request or API, or a browser to discover and reach that content.
Does the WebArena result mean hybrid agents always perform better?
No. It reports a result for the paper’s WebArena experiments. It does not establish that the same improvement applies to every website, model, or deployed task.
When should an agent use screenshots instead of extracted text?
Use screenshots when visual appearance or visible state is part of what the agent must inspect. When the task is to read prose or return specific data, Markdown or structured extraction may be a more direct representation.
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