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research.topic-deep-researcher

Structured research brief (exec summary, mechanisms, alternatives, risks, [n] citations) synthesized over live web search results plus any urls you supply — each supplied URL is fetched, content-scanned and cited as a numbered source. It is a $0.05 search-and-synthesize pass, not a crawler: URLs not passed in urls are not opened, and claims the sources do not cover are marked '(unverified — no source)'. Settlement proof: ProofOfSettledOutcome (kind 30120). Deeper than research.topic-news-scanner; web + supplied documents vs content.youtube-research's video-only pool. Refuses, with no charge, when ≥5 fetched web sources cannot be fetched. (x402: $0.05 USDC per call)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNoTask/query text for this SKU

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and does so well: it discloses cost ($0.05 USDC x402), the refusal-without-charge behavior for ≥5 unfetchable sources, the '(unverified — no source)' marking policy, and the ProofOfSettledOutcome (kind 30120) settlement artifact. These are exactly the behavioral traits an agent needs before invoking a paid tool.

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 what the tool produces, then cost, then routing guidance. Dense but nearly every clause earns its place; the parenthetical settlement/x402 details add minor clutter for a single-tool read.

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?

No output schema exists, so the description correctly compensates by enumerating the return shape (exec summary, mechanisms, alternatives, risks, [n] citations) and the source-traceability rules. Combined with pricing and refusal semantics, an agent has everything needed to call and interpret it.

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?

Only one parameter exists and schema description coverage is 100%, so the schema already covers it. The description adds useful semantics about supplied `urls` (fetched, content-scanned, cited as numbered sources), but `urls` is not present in the declared input schema, creating a mild mismatch rather than enriched schema documentation.

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 product (structured research brief with exec summary, mechanisms, alternatives, risks, citations) over a specific mechanism (live web search + supplied URLs), and explicitly contrasts itself with research.topic-news-scanner and content.youtube-research. An agent can distinguish it from all nearby siblings without opening a schema.

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 names alternatives and the axis of differentiation: 'Deeper than research.topic-news-scanner; web + supplied documents vs content.youtube-research's video-only pool.' It also states a hard exclusion ('not a crawler: URLs not passed in `urls` are not opened') and a no-charge refusal condition, giving both when-to-use and when-not-to-use.

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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