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Deep research report: plans several searches, reads up to 8 sources and writes a structured Markdown report (summary, key findings, details, open questions, numbered sources) with inline citations. Takes 20 to 60 seconds. Costs $0.10 USDC per call (x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesResearch topic or question

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), so the bar is lower, and the description adds genuinely new operational facts: 20–60s wall time, a per-call price, and an x402 payment requirement. What is missing is failure behavior (timeouts, source unavailability) and whether the report is returned inline or stored.

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?

Two dense sentences with zero filler: the process and output shape come first, then the practical constraints (time, cost). Every clause carries new information.

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 carries the burden of describing the return value, and it does so by listing the report sections and citing inline citations. Time and cost are covered; only edge-case behavior (what happens on sparse results or payment failure) is unaddressed.

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?

There is a single required parameter whose schema description ('Research topic or question') is already complete at 100% coverage, so the schema does the work. The description adds nothing about how the topic string is interpreted (question vs. keyword, breadth), leaving this at the baseline 3.

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?

It states a concrete verb and resource (plans searches, reads up to 8 sources, writes a structured Markdown report) and enumerates the report sections, so the agent knows exactly what it gets back. The gap is sibling differentiation: with dozens of adjacent tools (answer, ask, report_market, report_company, summarize, search), nothing says how this differs from them.

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

Usage Guidelines3/5

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

There is no explicit when-to-use or when-not-to-use statement, and no alternative is named. The latency and price disclosure ('20 to 60 seconds', '$0.10 USDC') implicitly signals 'use only for genuine deep-research needs', which is useful decision context but not stated 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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