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maginary-mcp

Search parameters

search_parameters
Read-onlyIdempotent

Text-search over parameter names, aliases, descriptions, values, examples.

Args:
    query: Substring match, case-insensitive.
    category: Optional single-category restriction.
    include_reserved: Whether to include ``unimplemented`` parameters.

Returns:
    Dict with ``count``, ``source`` (``live`` vs. ``bundled-snapshot``),
    and ``parameters`` (ordered as they appear in the catalog).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch term (case-insensitive substring match).
categoryNoFilter by category, e.g. composition, video, model.
include_reservedNoInclude unimplemented (blocked) parameters.

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 indicate readOnly, idempotent, and non-destructive behavior, so the description adds value by disclosing search semantics (case-insensitive substring), the inclusion of unimplemented parameters via include_reserved, and the return distinction between live and bundled-snapshot sources. These details go beyond what the annotations provide.

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?

The description is compact, front-loaded with the core purpose, and uses a clear Args/Returns structure. Every sentence contributes meaningful information without repetition or filler.

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?

The tool is simple, has an output schema, and all parameters are documented. The description fully covers search behavior, parameter roles, and return structure, including the live vs. bundled-snapshot source field and ordering guarantee. Nothing needed to invoke the tool 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description mostly mirrors the schema, though it adds useful nuance such as 'single-category restriction' and clarifies that include_reserved covers 'unimplemented' parameters. This is adequate but does not substantially exceed the schema's existing documentation.

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?

The description clearly states a specific verb ('Text-search') and a specific resource (parameter names, aliases, descriptions, values, examples), which distinguishes it from sibling tools like list_parameters or get_parameter. It also explains the search semantics in the first sentence, making the tool's role immediately obvious.

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 establishes clear context: it is for substring-based text search across parameter metadata. It does not explicitly name sibling tools or state when not to use them, but the 'Text-search' framing and the parameter-focused scope are sufficient to guide selection in most cases.

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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