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Window Sticker

Which makes are covered

which_makes_are_covered
Read-only

The 20 makes that return an original factory window sticker, by source, with the model years each answers for and the last day it returned a label. Every other make gets a specification decode only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
asOfYes
notesYes
sourcesYes
coverageUrlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedOutput schema / properties / sources / items / properties / heldCopiesOnly
      Removed value: -{
      -  "description": "get_window_sticker returns only labels we already hold.",
      -  "type": "boolean"
      -}
    • changedOutput schema / properties / sources / items / required
      Previous value: -[
      -  "source",
      -  "makes",
      -  "modelYears",
      -  "lastConfirmed",
      -  "note",
      -  "heldCopiesOnly",
      -  "paused"
      -]New value: +[
      +  "source",
      +  "makes",
      +  "modelYears",
      +  "lastConfirmed",
      +  "note",
      +  "paused"
      +]
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavioral context beyond the annotations: it explains the coverage boundary (only 20 makes) and what happens for every other make (specification decode only), which shapes how an agent interprets results.

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 tight sentences, front-loaded with the core content ('the 20 makes that return...') and the scope/fallback constraint placed last. No filler or redundant restatement of the title.

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 an output schema present, return-value structure need not be explained, and annotations cover safety. The description supplies the coverage semantics that the schema cannot convey, leaving only minor gaps (e.g., no explicit pointer to the sibling lookup flow).

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 tool takes zero parameters, so there are no parameter semantics to document; baseline 4 applies. The description correctly focuses on output scope instead of inventing parameter detail.

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 concretely what the tool returns: the list of 20 makes eligible for an original factory window sticker, including per-source, model years, and last-eligible date. It implicitly contrasts with the other make-universe tools (only 20 makes qualify), but does not name the siblings get_window_sticker or why_no_sticker explicitly.

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?

Usage is implied rather than stated: an agent can infer this is the coverage-lookup step before calling get_window_sticker, and the closing sentence clarifies the fallback for non-covered makes. There is no explicit when-to-use/when-not or named alternative, so it stays at the implied level.

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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