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Mahonia

One catalog product, every variant

get_catalog_product
Read-onlyIdempotent

One product's variants (sizes, lengths, temperature ratings) with the cited weight and source of each. Give a catalog id from search_catalog, or the brand and product name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoA catalog row id; its siblings are the other variants.
nameNoThe product name without brand or variant.
brandNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. With no output schema, the description carries weight by disclosing the payload ('with the cited weight and source of each'), telling the agent the response includes provenance per variant rather than raw specs.

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, zero filler. The return payload leads, followed by the input contract, so both the 'why call it' and 'how to call it' land immediately.

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?

A read-only, three-parameter lookup with no output schema or nested objects; the description covers the return content and both input modes, which is nearly everything an agent needs. The sole gap is that 'brand' has no documentation anywhere.

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?

Schema coverage is 67% and leaves 'brand' undescribed. The description compensates by explaining the two input strategies (id, or brand+name) that the schema lists but does not relate, and clarifies that id's siblings are the other variants via the id description.

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?

States a specific resource ('one product's variants') and enumerates what comes back ('sizes, lengths, temperature ratings... cited weight and source'), so an agent knows this is a variant-expansion lookup rather than a search. It distinguishes itself from search_catalog by naming the latter as the id source, though it never explicitly contrasts the two.

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?

Gives concrete invocation guidance: 'Give a catalog id from search_catalog, or the brand and product name,' which tells the agent both accepted input modes and routes it to search_catalog when it lacks an id. No explicit when-not-to-use statement, but the usage context is 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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