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AIsa Web Search & Research

Search Web Content

post_scholar_search_web
Destructive

Search the open web and get back a lean result list. ⚠️ Despite being a POST, parameters go in the query string — query (required), max_num_results (default 10, max 100), and as_ylo/as_yhi for a year range. A JSON body is not accepted. Returns a search id and results[] carrying only title, link and snippet. Measured at about 4 seconds for a roughly 600-byte response. Its virtue is how little it returns, which suits an agent that only needs to know what exists. It gives you no page text — if you need the content, post_tavily_search returns it in the same call. Keep the id: it is what post_scholar_search_explain needs.

Published reference price: $0.01 USD per successful request. Account-specific pricing and final settlement may differ.

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query for scholarly materials
as_yhiNoYear of publication upper bound
as_yloNoYear of publication lower bound
max_num_resultsNoMaximum number of search results to return, up to 100

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Discloses a non-obvious transport quirk (POST but parameters in the query string, JSON body rejected), the exact return shape (id plus results[] with title/link/snippet only), approximate latency and payload size, and the absence of page text. Annotations declare destructiveHint=true and readOnlyHint=false, and the description is consistent with a network-calling search rather than contradicting them.

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?

Front-loaded with the action and the transport warning, and the routing hint to post_tavily_search lands early. A few sentences are stylistic filler ("Its virtue is how little it returns") and the pricing comment block adds noise, so it is efficient but not waste-free.

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?

An output schema exists, yet the description still pins down the practical contract: transport method, required query, result fields, the returned id and its downstream use, cost, and expected latency. Nothing an agent needs in order to invoke and chain this call correctly is left implicit.

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 coverage is 100%, so the baseline is 3, but the description adds genuinely useful calling-convention detail: the parameters must go in the query string, a body is not accepted, and it restates the default (10) and ceiling (100) in prose. That is meaningfully beyond the schema's field-level descriptions.

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

Purpose4/5

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

States a specific verb and resource ("Search the open web and get back a lean result list") and characterizes the output shape, so the agent knows this is a lightweight web search rather than a content-fetching tool. It does not differentiate itself from the similarly-named siblings post_scholar_search_scholar and post_scholar_search_mixed, which an agent would otherwise confuse it with.

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

Usage Guidelines4/5

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

Gives a clear selection rule: use this when you only need to know what exists, and use post_tavily_search when you need page content, plus a follow-up hook (keep the id for post_scholar_search_explain). It stops short of explicit when-not guidance against the other scholar search variants listed as siblings.

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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