Search the live web and return ranked results (title, url, snippet) — fast, fresh, real-time web search for one focused lookup. Set topic to news for news-focused results. Pass highlight to get a ranked snippet per result, or full_content to pull the cleaned page body inline (heavier — costs more context). Narrow with domain / text include-exclude filters, a language filter (ISO 639-1 codes), and a time window (published/crawled start_time/end_time, or a relative time_range). Set include_images to return image URLs per result.

USE FOR a single focused lookup: one fact, one entity, one document. If the question spans several independent subtopics, load and use broad_search instead — a sequence of search calls is slower and gives worse coverage than one fan-out. To read a page you already have the URL for, use extract.

keywords: web search, search the web, look up, find, check, fact, current information, latest, news, source, url, real-time

Search recent news and return ranked articles (title, url, snippet) — current events, headlines, timely reporting. This is search locked to topic: news; same options as search (domain / text filters, language filter, time window, highlight / full_content, media) except topic, which is fixed to news.

For a single news lookup this is the right tool. For a multi-angle news question ("what shipped across the industry this month", "how are different outlets covering X"), use broad_search with topic=news instead of looping news_search.

keywords: news search, latest news, headlines, current events, breaking news, recent, today, this week, press coverage

Search the web across many angles in one call — for comparisons, research, surveys, and questions with several distinct parts. Expands your question into multiple sub-queries and runs them concurrently.

USE WHEN the question has multiple distinct parts or entities that one search cannot cover:

• comparing vendors / products / pricing across many sources

• literature reviews, market or landscape surveys

• open-ended "what are the options for X" / "how do people solve Y"

• a question that clearly decomposes into 3+ independent sub-questions

• multi-angle questions about recent events ("what shipped across the industry this month") — set topic=news, do NOT loop news_search

DO NOT USE for:

• a single fact, entity, or document → use search

• re-running a disappointing search → do NOT call broad_search twice; follow up with a targeted search or extract on the specific gaps

• reading a page you already have the URL for → use extract

• a straight A-vs-B comparison of two known entities → two targeted search calls are cheaper and more controllable

COST: fans out into max_queries concurrent searches — roughly Nx the cost and notably higher latency than a single search. When in doubt, prefer search.

QUERY: pass one natural-language question (max 500 chars). Resolve pronouns and references from the conversation first — "how does it compare to the other one" is a useless query. Do NOT pre-split into sub-queries; that is this tool's job. For broader coverage raise max_queries rather than calling repeatedly. Per-sub-query options (count, topic, language filter, domain / text filters, time window, highlight / full_content, media) match search and apply to every sub-query.

RESULTS are grouped per sub-query and NOT deduplicated — the same URL may appear under several sub-queries.

max_queries: 3-5 focused comparison (2-3 entities) | 5-10 multi-facet research | 10-20 landscape scan | 20-30 exhaustive survey

For a single focused lookup use search; to read a specific page use extract.

keywords: web search, search the web, look up, find information, research, compare, comparison, versus, alternatives, options, landscape, survey, market research, pricing, latest, current information, multi-part question

Read one or more web pages by URL and return clean, LLM-ready content (markdown or text). By default (no query) it returns each page's full content — this is what you want in almost all cases. Only pass query when the user explicitly asks to fetch relevance-ranked snippets for a specific topic; doing so returns highlights INSTEAD of the full body, so the content will be partial. Every result also includes a category (topical) and page_structure (typology) classification. Bare hosts like 'octen.ai' are auto-normalized to https. Cached when fresh.

Use this when you already have the URL(s). To find pages first, use search or broad_search.

keywords: read page, fetch url, scrape, page content, article text, parse webpage, extract, read article, url content, open link

Find images on the web by text query OR by a reference image — returns ranked results (title, source page, dimensions, thumbnail, description, summary). In Beta; contact us to request beta access. Pass exactly one of: a text query, an image_url (a picture already on the web), or image_data (base64, for a picture you hold). Never more than one. Set topic to design for UI design references — each result then carries a structured style summary and an html_snippet for building/restyling frontends. Use this when the user wants pictures, photos, diagrams, screenshots, or visual references — not for general text web search.

keywords: find images, image search, photos, pictures, screenshots, visual reference, diagram, icon, illustration, UI design, reference image

Find videos on the web by text query — returns ranked results (title, source page, cover image, duration, matching segment, authors, description). In Beta; contact us to request beta access. Pass a text query. Use this when the user wants to find videos, clips, footage, tutorials, or a specific moment within a video — not for general text web search.

keywords: find videos, video search, clips, footage, youtube, tutorial video, watch, movie, video clip