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срезAI — Search API for AI agents

by ru.srezai
OverviewAdmin

Веб-поиск / Web search

web_search
Read-only

Ищет страницы в живом вебе по текстовому запросу и возвращает ранжированный список: заголовок, ссылка, фрагмент. Сильное покрытие русскоязычного веба.

Когда: нужны свежие факты, ссылки или данные новее вашей отсечки знаний. Когда не: адрес страницы уже известен — это read_url; нужны 2–5 конкретных значений — extract; нужен готовый разбор темы со сносками — deep_research. Возвращает: до 30 результатов текстом, без содержимого страниц. С excerpts: true добавляет реальный текст топ-страниц (+2–4 с), это часто экономит последующий вызов read_url. Цена: 1 кредит за вызов, независимо от num. Выдача живая, поэтому повтор того же запроса даёт другой результат и списывается снова.

Searches the live web by a text query and returns ranked results: title, link, snippet. Strong coverage of the Russian-language web.

Use when: you need fresh facts, links or data past your knowledge cutoff. Do not use when: you already know the page URL — that is read_url; you need a handful of specific values — extract; you need a written answer across many sources — deep_research. Returns: up to 30 results as text, without page content. With excerpts: true it also pulls the actual text of the top pages (+2–4 s), which often saves a follow-up read_url. Cost: 1 credit per call regardless of num. Results are live, so repeating the same query returns different results and is billed again.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNoСколько результатов (1–30) / How many results (1–30)
depthNoГлубина: auto (по умолчанию, больше движков и результатов) или flash (быстрее, узкая выдача — для одного факта). / Depth: auto (default, more engines and results) or flash (faster, narrow — for a single fact).
queryYesПоисковый запрос / Search query
categoryNoКатегория / Category: general, news, it, science
excerptsNoЗабрать реальный текст топ-страниц под запрос (медленнее на пару секунд, но даёт готовый контент для ответа без доп. переходов). По умолчанию выкл. / Pull the actual text of the top pages for this query (a couple of seconds slower, but gives ready content without extra calls). Off by default.
languageNoЯзык / Language: auto, ru, en
timeRangeNoСвежесть / Recency: all, day, week, month, year
excludeDomainsNoИсключить эти сайты и их поддомены: ["pinterest.com"]. До 10 доменов. / Exclude these sites and their subdomains. Up to 10 domains.
includeDomainsNoИскать только на этих сайтах, вместе с поддоменами: ["habr.com", "vc.ru"]. До 10 доменов. / Search only these sites, including subdomains. Up to 10 domains.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / timeRange / description
      Previous value: -"Свежесть / Recency: '', day, week, month, year"New value: +"Свежесть / Recency: all, day, week, month, year"
  2. Changed1 schema field changed
    • changedInput schema / properties / timeRange / enum
      Previous value: -[
-  "",
-  "day",
-  "week",
-  "month",
-  "year"
-]New value: +[
+  "all",
+  "day",
+  "week",
+  "month",
+  "year"
+]
  3. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true and openWorldHint=true, and the description adds complementary context: results are live so repeats return different results, each call costs 1 credit regardless of num, and excerpts: true pulls page text and can save a follow-up read_url. This goes beyond the structured annotations and matches idempotentHint=false.

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

Conciseness4/5

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

The description is front-loaded with the core behavior and uses clear labeled sections (When/When not, Returns, Cost). It is longer than minimal and bilingual, which adds redundancy, but every substantive point earns its place and the structure makes it scannable.

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?

With no output schema, the description explains the return shape ('up to 30 results as text... title, link, snippet') and its limits ('without page content'). Parameter coverage is complete via the schema, and the description covers cost, liveness, and routing, so an agent has everything needed to invoke it correctly.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds extra semantic value by explaining the cost behavior of num ('1 credit per call regardless of num') and the practical trade-off of excerpts: true ('often saves a follow-up read_url'), which helps the agent choose parameters more intelligently than the schema alone.

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?

States a specific verb and resource: 'Searches the live web by a text query and returns ranked results: title, link, snippet.' Also differentiates from siblings by being the general web-search entry point, and the phrase 'Strong coverage of the Russian-language web' adds a distinguishing scope cue.

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?

Explicitly states when to use ('fresh facts, links or data past your knowledge cutoff') and when not to, naming three alternatives with their conditions: read_url for known URLs, extract for 2–5 concrete values, deep_research for a synthesized answer across sources. This is exemplary routing guidance.

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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