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market_for_rent_grouped

Retrieve grouped card-rental price and quantity summaries, including season and daily quantities, to analyze rental market trends.

Instructions

Read grouped card-rental price and quantity summaries, including season_qty and daily_qty. The observed response had 1710 groups; only a bounded leading portion is returned. Makes one logical GET request Does not auto-fetch continuation pages. Required inputs reflect tool policy as well as measured upstream requirements. Other declared filters are forwarded as supplied; their effectiveness is not implied by the schema. Array responses are locally limited to 100 rows and 256 KiB, with truncation reported in text and metadata. Oversized records are refused without partial fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly covers pagination (no auto-fetch, bounded leading portion), response limits (100 rows, 256 KiB), truncation reporting, and refusal of oversized records. This gives the agent a clear and complete picture of runtime 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?

The description is a single dense paragraph that front-loads the purpose and then details limitations. Each sentence adds value, but the density might be slightly overwhelming. It is appropriately sized for the complexity and does not waste words.

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?

For a tool with no parameters and no output schema, the description covers all essential aspects: what it does, pagination behavior, limits, truncation, and failure handling. An agent can invoke it correctly without needing additional context. The note about forwarded filters and their effectiveness is particularly useful.

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

Parameters4/5

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

The input schema has zero parameters, so there is nothing to explain. The description mentions 'required inputs' but that appears to refer to upstream requirements rather than schema parameters. Baseline for 0 params is 4, and the description adds no conflicting or redundant info.

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 verb ('Read') and resource ('grouped card-rental price and quantity summaries'), and names the included fields (season_qty, daily_qty). This clearly distinguishes it from sibling tools like market_for_sale_grouped and market_active_rentals, which target different data.

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 description explains what the tool does but provides no explicit guidance on when to use it versus alternatives such as market_active_rentals or market_query_grouped. There is no mention of conditions that would favor this tool, nor any exclusions. The purpose implies a use case, but the agent is left to infer the selection criteria.

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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