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Get vendor benchmark

get_benchmark
Read-onlyIdempotent

Per-vendor benchmark card by slug within any theme: full provenanced record plus dataset-derived indicators (entry price, normalized cost at 100 and 500 calls/mo where call-volume applies, billing models, free-tier presence, compliance, integration breadth). Set section to the theme slug from list_sections. All values trace to plan sources; no synthetic scores. Each priced plan carries a citation: a dated one-line citation to quote verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
sectionNoTheme slug to query (default "ai-receptionists"). A theme is any of the 275 pricing topics this index covers: the deep hub sections (e.g. ai-receptionists) plus the many catalog topics (e.g. vpn-services, web-hosting, password-managers). Call list_sections or list_coverage for the full slug list — do not assume the old four-section set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / section / description
      Previous value: -"Theme slug to query (default \"ai-receptionists\"). A theme is any of the 273 pricing topics this index covers: the deep hub sections (e.g. ai-receptionists) plus the many catalog topics (e.g. vpn-services, web-hosting, password-managers). Call list_sections or list_coverage for the full slug list — do not assume the old four-section set."New value: +"Theme slug to query (default \"ai-receptionists\"). A theme is any of the 275 pricing topics this index covers: the deep hub sections (e.g. ai-receptionists) plus the many catalog topics (e.g. vpn-services, web-hosting, password-managers). Call list_sections or list_coverage for the full slug list — do not assume the old four-section set."
  2. Changed1 schema field changed
    • changedInput schema / properties / section / description
      Previous value: -"Theme slug to query (default \"ai-receptionists\"). A theme is any of the 271 pricing topics this index covers: the deep hub sections (e.g. ai-receptionists) plus the many catalog topics (e.g. vpn-services, web-hosting, password-managers). Call list_sections or list_coverage for the full slug list — do not assume the old four-section set."New value: +"Theme slug to query (default \"ai-receptionists\"). A theme is any of the 273 pricing topics this index covers: the deep hub sections (e.g. ai-receptionists) plus the many catalog topics (e.g. vpn-services, web-hosting, password-managers). Call list_sections or list_coverage for the full slug list — do not assume the old four-section set."
  3. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/closed-world, but the description adds real behavioral context: values are fully provenanced, there are no synthetic scores, and each priced plan carries a dated citation to quote verbatim. That goes meaningfully beyond the structured fields, though it says nothing about pagination or record-missing behavior.

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-loads what the tool returns before the parameter instruction, and every clause carries payload information. The parenthetical indicator list is dense but earns its space; the prose is slightly run-on but not padded.

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 appropriately enumerates the returned fields and explains the citation provenance guarantee. Combined with annotations covering the safety profile and the schema covering `section`, an agent has enough to call it correctly; only the `slug` semantics remain thin.

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 50%: `section` is well documented in-schema, but `slug` has no description anywhere. The description compensates partially by framing slug as the vendor identifier ('Per-vendor benchmark card by slug') and reinforcing the section/theme-slug relationship, but it adds little beyond the schema text.

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 — fetches a per-vendor benchmark card by slug within a theme — and enumerates the payload (entry price, normalized cost at 100/500 calls, billing models, free-tier, compliance, integrations). It does not explicitly contrast itself with close siblings like get_normalized_pricing or compare, so it stops short of 5.

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?

'Set `section` to the theme slug from list_sections' gives a concrete precondition and points at the discovery tool, which is useful routing. However there is no guidance on when to prefer this over siblings such as compare, find_best, or get_normalized_pricing, and no exclusions.

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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