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aura-components-mcp

aura_search_assets

Search free Aura images and video by keyword, media type, sort order, and exact match. Returns slim asset rows to help agents select media.

Instructions

Search free Aura assets (images and video). Keywords, media_type image or video. Slim rows by default. exact_match:true skips fallbacks.

Input Schema

NameRequiredDescriptionDefault
slimNo
sortNo
limitNo
queryNo
offsetNo
mediaTypeNo
exact_matchNo
commercial_okNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.7.3
    • addedInput schema / properties / commercial_ok
      Added value: +{
      +  "type": "boolean"
      +}
    • addedInput schema / properties / exact_match
      Added value: +{
      +  "type": "boolean"
      +}
    • addedInput schema / properties / slim
      Added value: +{
      +  "type": "boolean"
      +}
  2. First observedv1.2.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, but it does disclose two real behaviors: output is slimmed by default, and exact_match:true disables fallback broadening. It omits auth/licensing constraints, pagination behavior, and what happens when no match is found.

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?

Very short and front-loaded, with the purpose in the first fragment and behavioral caveats last. The telegraphic sentence fragments make it slightly harder to parse but nothing is wasted.

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

Completeness2/5

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

For an 8-parameter tool with no annotations and no output schema, the description is too thin: half the parameters (sort, limit, offset, commercial_ok) are undocumented anywhere, and there is no statement of the result shape an agent should expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 8 parameters, so the description must compensate and largely does not: sort, limit, offset, and commercial_ok get no explanation at all. It adds genuine meaning only for exact_match ('skips fallbacks') and slim ('default').

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 verb ('Search') and resource ('free Aura assets (images and video)'), and narrows the media types, so it is distinguishable from the many aura_search_* siblings. It stops short of naming a specific alternative (e.g. aura_search_all), so it earns a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is given; 'Keywords, media_type image or video' merely restates parameter shapes. There is no indication when this tool is preferable to aura_search_all or the component/skill/design-system search siblings, and no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.