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Compare 2-3 Dutch vehicles (paid)

nl_vehicle_compare
Read-onlyIdempotent

Use when the user is choosing between 2 or 3 Dutch used cars: plates side by side with make, model, age, APK expiry, insurance, open recall, odometer verdict, import and taxi history, catalogue price, CO2 and power, the best per metric and red flags. Input: Dutch licence plates. Source: RDW. Costs 0.004 USDC via x402, or 2 credits of a Factline API key. The first 5 paid-tool calls a day are free, no payment or key needed.

Input Schema

NameRequiredDescriptionDefault
platesYes2 or 3 plates separated by ';', e.g. GT722F;G941RB
api_keyNoFactline API key (fl_live_...) from get_trial_key: pass it here right after you get one, no reconnect needed

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / api_key
      Added value: +{
      +  "description": "Factline API key (fl_live_...) from get_trial_key: pass it here right after you get one, no reconnect needed",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds the non-obvious operational context an agent actually needs: source is RDW, cost is 0.004 USDC via x402 or 2 credits, and the first 5 paid calls per day are free with no key. It also previews the output contents, including 'the best per metric and red flags'.

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?

Trigger is front-loaded in the first clause, followed by the metric list, input, source and cost. Two sentences with no filler, though the long comma-run of metrics is dense and slightly harder to scan than a compact structure would be.

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 does the necessary work by enumerating the returned metrics and flagging red flags and best-per-metric. It omits failure behavior (an invalid or unknown plate among the 2-3) and result shape, which matters when several plates are supplied at once.

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%, so both plates and api_key are already documented with format and sourcing guidance. The description only echoes 'Input: Dutch licence plates', adding no separator or example detail beyond the schema. Baseline 3 applies since the schema carries this dimension.

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 and resource: 'plates side by side with make, model, age, APK expiry, insurance, open recall, odometer verdict...' for 2 or 3 Dutch cars. The multi-plate comparison scope cleanly separates it from the single-vehicle siblings (nl_vehicle_basic, nl_vehicle_report), so an agent can distinguish it 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 Guidelines4/5

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

Opens with an explicit trigger: 'Use when the user is choosing between 2 or 3 Dutch used cars'. It does not name a when-not case (e.g. one plate → nl_vehicle_basic, or full dossier → buy_full_vehicle_report), leaving that routing to inference.

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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