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NeuralVerge Business Intelligence

Gartner markets search

run_gartner_markets_search

Search Gartner Peer Insights markets (software categories) by keyword. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch term. e.g. data loss prevention
max_itemsNoMax items (up to 250) Default: 25.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / max_items / description
      Previous value: -"Maximum number of markets to return (1-250, default 25). Billed at 1 point per returned record."New value: +"Max items (up to 250) Default: 25."
    • changedInput schema / properties / query / description
      Previous value: -"Search term, e.g. 'data loss prevention'."New value: +"Search term. e.g. data loss prevention"
  2. Added

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose a genuinely useful trait the schema does not: the cost model '1 point per returned record,' which lets an agent manage budget via max_items. It says nothing, however, about return shape, pagination, or result ordering.

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 tight sentences, purpose front-loaded, with the cost disclosure in the second. No filler or repetition of schema content.

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

Completeness3/5

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

Adequate for a two-parameter search whose schema is fully documented and whose cost is disclosed, but it leaves the agent without routing guidance in a tool family containing several near-identical Gartner search/list endpoints. That is the main gap for an otherwise simple call.

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 coverage is 100%, and both parameters (query with an example, max_items with bounds and default) are fully documented in the schema. The description adds no syntax, format, or matching-behavior detail beyond 'by keyword,' so the baseline 3 applies.

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 (Search) and a precisely scoped resource ('Gartner Peer Insights markets'), with a helpful parenthetical clarifying that markets are software categories. It does not differentiate itself from siblings like run_gartner_categories or run_gartner_products_search, which an agent must disambiguate among.

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

Usage Guidelines2/5

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

The only usage signal is 'by keyword.' There is no when-to-use guidance, no exclusion of the close sibling run_gartner_categories, and no indication of when to prefer this markets search over a categories listing or a products search.

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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