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octen-mcp

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by Octen-Team

broad_search

Run multiple web searches concurrently by expanding a question into sub-queries for comparisons, research, surveys, and multi-part questions.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of results to return (1-100). Default 5.
queryYesSearch query. Max 500 chars.
topicNoSearch category: `general` for broad web search, `news` for news-focused results. Default general.general
formatNoFormat of returned content. Default text.text
timeoutNoRequest timeout in seconds (1-300). Defaults to 120s if unset. Raise it for large `max_queries` surveys, which legitimately take longer.
end_timeNoUpper bound for the time window, ISO 8601.
languageNoLanguages to filter results by, as ISO 639-1 codes. Empty = no filter.
highlightNoReturn a ranked highlighted snippet per result. Omit to use the server default.
safesearchNoAdult-content filter. Default strict.strict
start_timeNoLower bound for the time window, ISO 8601 (e.g. '2025-01-01T00:00:00Z').
time_basisNoWhich timestamp the time window filters against: page `published` date, last `crawled` date, or `auto`. Default auto.auto
time_rangeNoRelative time window (e.g. `week`, `month`). Mutually exclusive with `start_time`/`end_time` — if both are given, the absolute range wins.
max_queriesNoUpper bound on the number of sub-queries generated (1-30). Default 5 — raise toward 30 for surveys / deeper research, lower for a tighter search.
exclude_textNoDrop results whose content contains any of these strings. Max 5, each ≤30 chars.
full_contentNoReturn the cleaned full page body per result. Heavier than `highlight` — use only when the snippet isn't enough. Omit to use the server default (off).
include_textNoOnly return results whose content contains all of these strings. Max 5, each ≤30 chars.
include_imagesNoReturn image URLs (and a cover image) found on each result page.
include_videosNoReturn video URLs found on each result page.
exclude_domainsNoDrop results from these domains. Max 150, each ≤30 chars.
include_domainsNoOnly return results from these domains (e.g. 'arxiv.org'). Max 1000, each ≤30 chars.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description fully bears the transparency burden and does so excellently. It discloses the fan-out into max_queries concurrent searches, cost/latency implications, result grouping per sub-query, and lack of deduplication. It also notes how per-sub-query options match the search tool, giving a complete behavioral picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with clear sections (USE WHEN, DO NOT USE, COST, QUERY, RESULTS) and bullet lists. Every sentence carries substance: query guidance, cost warning, max_queries scale, and a closing reminder. Though long, the length is justified by the tool's complexity and the need to prevent overuse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 20-parameter tool with 100% schema coverage and no output schema, the description covers the core decision factors: when to use, cost, query handling, result grouping, and per-sub-query options. It leaves no critical gaps for an agent to misuse the tool, and it addresses the main failure modes (duplicate calls, vague queries).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, upholding the baseline, but the description significantly enriches parameter understanding: query must be a single natural-language question, pronouns resolved, no pre-splitting; max_queries has usage ranges (3-5 comparison, 5-10 research, etc.); and per-sub-query options apply globally. This adds practical value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches the web across many angles, expanding into multiple sub-queries. It explicitly distinguishes from single-search tools by mentioning comparisons, research, surveys, and multi-part questions, and it names alternatives like search, extract, and news_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit USE WHEN scenarios with concrete examples (comparing vendors, literature reviews, open-ended options), a DO NOT USE list that names alternatives (search, extract, news_search), and cost/latency guidance with a clear preference for single search when in doubt. This gives an agent precise decision criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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