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maginary-mcp

Get parameter

get_parameter
Read-onlyIdempotent

Return the full record for a single parameter (canonical name or alias).

Args:
    name: Parameter name with or without leading ``--`` (e.g. ``ar``,
        ``--ar``, ``aspect``). Case-insensitive.

Returns:
    The parameter dict. Not-found is an ``isError`` result — surface it
    rather than fabricating a param.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesParameter name with or without --, e.g. ar, --ar, aspect.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds valuable behavioral context: it specifies the return type ('parameter dict') and error handling ('Not-found is an isError result — surface it rather than fabricating a param'). This goes beyond the annotations and helps the agent avoid incorrect behavior.

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?

Concise and well-structured with an Args/Returns format. The main purpose is front-loaded, and every sentence adds value. No fluff or redundancy.

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

Completeness5/5

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

For a simple single-parameter get with an output schema present, the description covers everything an agent needs: the name format, case-insensitivity, return type, and error behavior. No important operational details are missing.

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 100%, so the baseline is 3. The description adds meaningful extra semantics: it clarifies the name can be canonical or alias, that leading '--' is optional, and that matching is case-insensitive. This enriches understanding beyond the schema's terse example.

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 ('Return') and resource ('full record for a single parameter'), and explicitly notes it accepts canonical name or alias. This distinguishes it from siblings like list_parameters and search_parameters by focusing on a single known parameter.

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?

Implies usage for a single parameter but does not explicitly name alternatives or conditions for choosing this tool over list_parameters or search_parameters. The context signals show these siblings, and the description could have added 'use search_parameters when you don't know the exact name' for clearer routing.

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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