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Window Sticker

Why no window sticker

why_no_sticker
Read-only

Why a make, or a make and model year, has no window sticker here, and where to get one instead. Covers makes we get labels for (Ford only while a car is new, Toyota from 2025) and makes we don’t (Honda, Mazda, Tesla).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesMake name, such as Ford, Chevrolet or Honda.
model_yearNoModel year, such as 2019. Optional; the Toyota and Lexus answer depends on it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYes
stepsYes
reasonYes
sourceYes
moreUrlYes
warningYes
headlineYes
modelYearYes
supportedYesWe have a source of original labels for this make.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The annotations already signal read-only and open-world behavior. The description adds useful behavioral context beyond that: coverage varies by make, Ford stickers exist only while a car is new, Toyota coverage starts in 2025, and the tool also points to where a sticker can be obtained instead. No contradiction with the annotations.

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 sentences, front-loaded with the exact question the tool answers, followed by concrete coverage examples. No filler or redundant restatement of the tool name or schema.

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?

Given a simple read-only explanation tool with two parameters, full schema coverage, and an output schema, the description covers purpose, scope, caveats, and fallback guidance. It could have explicitly referenced sibling tools, but nothing essential for invoking it correctly is missing.

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?

The schema already documents both parameters fully, with make described by example and model_year marked optional with the Toyota/Lexus dependency. The description adds extra examples (Ford, Toyota, Honda, Mazda, Tesla) and confirms model-year relevance, but does not need to add more because schema coverage is complete.

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?

The description states a clear purpose: explaining why a make or make/model-year has no window sticker and where to get one instead. It differentiates from get_window_sticker by focusing on absence rather than retrieval, and although it never names sibling tools, the scope is specific enough for an agent to identify the tool's role.

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 provides clear context for when the tool applies: when a window sticker is missing, with coverage details by make and model-year. It does not explicitly exclude cases or name alternatives like which_makes_are_covered, but the intended usage is strongly implied and not misleading.

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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