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dialogbrain

by io.github.saloprj
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web_research

Read-onlyIdempotent

Answer a research question from live web sources in one call — returns a synthesized answer with numbered [N] citation markers and a citations array of {url, title, index}. Supports recency and domain filters. Use for questions needing current, sourced information (news about a company, market state, comparisons). For raw search result links use web.search; mode='deep' runs minutes-long exhaustive research — only when explicitly requested.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoResearch depth: 'quick' (default, seconds, cheapest), 'pro' (harder questions, better sourcing), 'deep' (autonomous multi-step research, takes minutes — only when the user explicitly wants an exhaustive report).quick
queryYesResearch question. Specific scoped questions outperform vague keywords.
domainsNoRestrict search to these domains (max 10), e.g. ['coindesk.com', 'cointelegraph.com']. Prefix with '-' to exclude a domain.
recencyNoOnly use sources from this window. Omit for no limit.
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / in_workspace
      Added value: +{
+  "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
+  "type": "integer"
+}
  2. Added
  3. Removed
  4. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, openWorld, non-destructive), so the bar is lower; the description adds genuinely useful context beyond them, namely the return format (numbered citation markers plus citations array) and the cost/latency tradeoff of deep mode. It does not mention rate limits, caching, or source-quality caveats, which keeps it from a 5.

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?

It is a single dense paragraph that front-loads what the tool returns before covering filters, alternatives, and the deep-mode caveat. Every clause carries information, though the paragraph is packed enough that a short bulleted split would scan faster.

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

Completeness4/5

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

With no output schema, the description usefully describes the return shape itself, and it covers routing versus the web_search sibling. It omits anything about result freshness guarantees, source quality, or failure modes, so it is strong but not exhaustive for a research tool of this complexity.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all five parameters including mode, recency, and domain filtering. The description only restates that recency and domain filters exist and echoes the deep-mode cost warning, adding little beyond what the schema states.

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 states a specific verb (answer a research question) plus resource (live web sources) and describes the output shape (synthesized answer with [N] markers and a citations array). It also explicitly differentiates itself from the sibling web_search tool for raw links.

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?

It names the alternative (web.search for raw result links) and gives explicit conditions for each mode, including the warning that mode='deep' runs minutes-long research and should only be used when explicitly requested. It also lists concrete use cases (news about a company, market state, comparisons).

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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