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TKMD

ReftrixMCP

by TKMD
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

part.search

Read-onlyIdempotent

Search UI component parts using hybrid text and vector search. Filters include part type, search mode, audience, and industry.

Instructions

UIコンポーネントパーツ（ボタン、カード、リンク等）をセマンティック検索します。テキストクエリ（e5-base + full-text）によるハイブリッド検索を提供。partType（16種類）やsearchMode（visual/text/hybrid）でフィルタリング可能です。 / Search UI component parts (buttons, cards, links, etc.) by text query. Provides hybrid search via e5-base + full-text. Filterable by partType (16 types) and searchMode (visual/text/hybrid).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoタグフィルター / Tag filter
limitNo取得件数（1-100、デフォルト: 20） / Result limit (1-100, default: 20)
queryNoテキスト検索クエリ（1-500文字） / Text search query (1-500 chars)
offsetNoオフセット（0以上、デフォルト: 0） / Offset (0+, default: 0)
audienceNoターゲットオーディエンス（例: b2b, b2c, enterprise） / Target audience filter
industryNo業種フィルター（例: tech, finance, healthcare） / Industry filter
image_urlNo画像URLによるビジュアル検索（将来対応予定） / Visual search by image URL (future support)
part_typeNoパーツタイプでフィルター（16種類） / Filter by part type (16 types)
search_modeNo検索モード（デフォルト: hybrid） / Search mode (default: hybrid)hybrid
web_page_idNoWebページIDでフィルター / Filter by web page ID
min_similarityNo最小類似度閾値（0-1、デフォルト: 0.3） / Min similarity threshold (0-1, default: 0.3)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv0.3.0
    • addedInput schema / properties / audience
      Added value: +{
+  "description": "ターゲットオーディエンス（例: b2b, b2c, enterprise） / Target audience filter",
+  "maxLength": 100,
+  "type": "string"
+}
    • addedInput schema / properties / industry
      Added value: +{
+  "description": "業種フィルター（例: tech, finance, healthcare） / Industry filter",
+  "maxLength": 100,
+  "type": "string"
+}
    • addedInput schema / properties / tags
      Added value: +{
+  "description": "タグフィルター / Tag filter",
+  "items": {
+    "maxLength": 50,
+    "type": "string"
+  },
+  "maxItems": 10,
+  "type": "array"
+}
  2. Addedv0.1.8

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already indicate readOnly and idempotent. The description adds details about the search models (e5-base, full-text) and future support for image search, but does not disclose additional behavioral traits beyond what 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with key information. However, it includes bilingual content that could be streamlined for brevity, but overall it is efficient.

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

Completeness3/5

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

Given the complexity (11 parameters, no output schema), the description covers the purpose and main filters but does not explain the return format, pagination, or edge cases. Annotations help but the description could be more complete.

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?

Input schema description coverage is 100%, so the description adds no extra meaning beyond parameter names and types. It mentions partType and searchMode but these are already in the schema.

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?

The description clearly states the tool performs semantic search of UI component parts with hybrid search, and lists filtering options. It distinguishes from sibling tools by focusing on UI parts, but does not explicitly differentiate from other search tools.

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?

The description lacks guidance on when to use this tool vs alternatives. It does not mention when not to use it or provide context for choosing it over other search tools on the server.

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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