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quote_land_cover_classification

Request a FREE commercial quote for: Land Cover Classification. Satellite-based land cover classification Returns a binding USD price and quote_id (valid 15 min); no execution yet and no credits consumed. Use execute_quote with the quote_id to run it — execution consumes prepaid credits. Requires an API key (X-API-Key or Authorization: Bearer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
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 explicitly states that this tool returns a binding USD price and a 15-minute-valid quote_id, performs 'no execution yet', consumes 'no credits', and requires an API key. It also warns that execution via execute_quote consumes prepaid credits, giving an agent a complete safety and cost profile.

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 relatively short and front-loads the core purpose. Each sentence serves a purpose: purpose, return/validity/no-execution, next-step routing, and authentication. However, the second sentence is a run-on that awkwardly combines capability, return value, and behavior, which reduces readability slightly.

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?

For a simple tool with no formal parameters and no output schema, the description covers the essential operational details: what is returned, validity period, cost behavior, the follow-up execution step, and authentication requirements. It does not document any optional input properties that the schema permits via additionalProperties, but this is a minor gap given the tool's simplicity.

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 formal properties and allows additionalProperties: true. Since parameter count is 0, the baseline is 4; the description does not need to explain parameters that don't exist formally. However, the description also does not clarify what additional properties (if any) might be expected, but this is a schema detail rather than a description deficiency.

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?

The description clearly states the verb 'Request a FREE commercial quote' and the resource 'Land Cover Classification', and adds the qualifier 'Satellite-based' to define the capability. This distinguishes it from sibling quote_* tools like quote_land_change_detection or quote_vegetation_health_index, so an agent knows exactly what product is being quoted.

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

Usage Guidelines4/5

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

The description gives clear context for when to use this tool: to obtain a binding price quote without executing a job. It explicitly instructs to use execute_quote with the returned quote_id for execution, which distinguishes this tool from its execution sibling. It doesn't explicitly exclude other quote_* tools, but the specific combination of product name and workflow makes the usage context sufficiently clear.

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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