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Get a model

get_model
Read-onlyIdempotent

All the data of one of the fridges in FridgeBase's comparison (by its slug) and the link to its page.

Input Schema

NameRequiredDescriptionDefault
slugYes
marketYesThe market: us = the United States (Amazon.com, in English), fr = France (Amazon.fr, in French). Each market has its own catalog.us

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / required
      Previous value: -[
      -  "slug"
      -]New value: +[
      +  "slug",
      +  "market"
      +]
  2. Changed1 schema field changed
    • addedInput schema / properties / market
      Added value: +{
      +  "default": "us",
      +  "description": "The market: us = the United States (Amazon.com, in English), fr = France (Amazon.fr, in French). Each market has its own catalog.",
      +  "enum": [
      +    "us",
      +    "fr"
      +  ],
      +  "type": "string"
      +}
  3. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive behavior, so little is left to disclose on safety. The description adds that the response is the full record plus a page link, which is useful since there is no output schema, but it says nothing about what happens for unknown slugs or that the catalog is market-scoped.

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?

A single sentence with the resource and key mechanism front-loaded; no filler. Slightly awkward phrasing ('one of the fridges in FridgeBase's comparison') but nothing wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter read tool with no output schema, the description covers what is fetched and that a page link is included. It is still incomplete on the market-scoping requirement and on not-found behavior, both of which an agent may need.

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 50%: 'market' is well documented in the schema (us/fr with Amazon domain and language), while 'slug' has no schema description at all. The description only restates that lookup is keyed by slug and does not explain its format or provenance, so it adds marginal value over the schema.

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 names a concrete resource and key ('All the data of one of the fridges ... by its slug') plus a return element ('the link to its page'), so an agent knows this is a single-model detail lookup. It does not name any sibling (search_models, compare_models, fetch), so the boundary with those tools is left implicit.

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?

'By its slug' implies the prerequisite (you must already have a slug, presumably from search_models) and the singular 'one of the fridges' implies detail retrieval rather than searching. There is no explicit when-to-use/when-not guidance and no mention of compare_models or search as alternatives.

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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