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Uwear

by ai.uwear
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Search Library

search_uwear_library
Read-onlyIdempotent

Universal hybrid retrieval across the user's visible Uwear library: garments, avatars/models, locations, ArtDirections, uploaded files, and generation results. This is a finder, not a recommender. Use short keyword queries (2 to 5 words), one concept per call, or an exact name/SKU/ID. Every word must match for lexical results; long sentences can return no lexical matches. A query describing one garment finds that garment, not complementary garments. Vector results stay close to the best match. Use this before opening the picker, e.g. 'SKU 42', 'urban art direction', 'summer denim', or 'studio model'. For saved outfits, retrieve matching garments first, then call list_outfits with clothing_item_ids or propose_outfits from the garment IDs. Returns stable typed IDs, ids_by_type, detail_tool/detail_arguments, and selection hints; for saved ArtDirections, use the returned art_direction_id in briefs. This combines current lexical metadata with maintained vector retrieval. Interactive searches do not refresh the index. indexed_count is always 0 here; it is not index coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of hybrid matches to return
queryYesShort keyword query: 2 to 5 words, one concept per call, or an exact name/SKU/ID. Every word must match for lexical results, so long sentences can return no lexical matches. Describing a garment finds that garment, not pieces to pair with it.
item_typesNoOptional item types to search. Omit to search clothing, avatars/models, locations, art directions, uploaded files, and generation results.
refresh_indexNoDeprecated compatibility input. No index refresh is performed, even when true. Search uses the maintained index and current lexical metadata. Leave false.
exclude_clothing_item_idsNoExclude these garment IDs after ranking and before the result limit; other item types are unaffected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / exclude_clothing_item_ids
      Added value: +{
+  "default": null,
+  "description": "Exclude these garment IDs after ranking and before the result limit; other item types are unaffected.",
+  "items": {
+    "type": "integer"
+  },
+  "maxItems": 100,
+  "type": "array"
+}
    • changedInput schema / properties / query / description
      Previous value: -"Hybrid retrieval query. Handles exact names/SKUs/IDs and natural-language visual or attribute intent."New value: +"Short keyword query: 2 to 5 words, one concept per call, or an exact name/SKU/ID. Every word must match for lexical results, so long sentences can return no lexical matches. Describing a garment finds that garment, not pieces to pair with it."
    • changedInput schema / properties / refresh_index / description
      Previous value: -"Force-refresh missing or stale index rows for currently visible library items before searching. Leave false for normal MCP use; search refreshes once automatically only when no accessible match is found."New value: +"Deprecated compatibility input. No index refresh is performed, even when true. Search uses the maintained index and current lexical metadata. Leave false."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses important behaviors: lexical matching requires every word to match, vector results stay close to the best match, interactive searches do not refresh the index, and indexed_count is always 0. It also states the shape of returned selection data, which matters because no output schema is present.

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?

The description is long but dense, front-loading the core purpose and usage before edge-case caveats. Almost every sentence earns its place, though the indexed_count caveat and repeated querying guidance push it toward the longer end of what is ideal.

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?

Because there is no output schema, the description compensates by explaining that it returns stable typed IDs, ids_by_type, detail_tool/detail_arguments, and selection hints, and by explaining how to use art_direction_id in briefs. It covers query constraints, index behavior, and sibling routing, leaving no critical gap for correct invocation.

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 value by providing concrete example queries ('SKU 42', 'urban art direction', 'summer denim') and clarifying query formulation behavior beyond the schema's phrasing, such as the one-concept-per-call rule and the exact-name/SKU/ID fallback.

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 opens with a specific verb and resource: universal hybrid retrieval across the user's visible Uwear library, and enumerates all covered item types. It also explicitly disambiguates from recommendation tools by saying 'This is a finder, not a recommender' and from outfit workflows by routing to list_outfits/propose_outfits.

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

Usage Guidelines5/5

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

It gives concrete when-to-use guidance: short 2-5 word queries, one concept per call, exact name/SKU/ID or before opening the picker, with examples. It names alternatives for saved outfits, instructing the agent to retrieve garments first and then call list_outfits or propose_outfits, which makes tool selection explicit.

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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