entry-offline-mcp

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entry_search_assets

Searches the offline Entry asset library for sprites, backgrounds, pictures, or sounds using Korean or English keywords and categories, and lists available categories.

Instructions

엔트리 기본 리소스 라이브러리 검색(오프라인 내장). kind='sprite'(오브젝트: 모양 여러 개+소리 포함), 'background'(배경 오브젝트), 'picture'(모양 단일 그림), 'sound'(소리). query는 한국어/영어 키워드(공백=AND). query 없이 list_categories=true면 카테고리 목록.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kind": "<kind>"
    },
    "name": "entry_search_assets"
  }
}

Input Schema

Name	Required	Description
`kind`	Yes
`limit`	No
`query`	No
`offset`	No
`category`	No	예: 'people', 'animal', 'background/background_nature', '배경/실내'
`list_categories`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 13, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations, the description carries the full burden and does disclose useful behavior: the library is offline/embedded, and kind='sprite' returns a composite object with multiple shapes plus sounds while 'picture' is a single shape. It says nothing about pagination via limit/offset, result ordering, or maximum result counts.

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?

A single dense paragraph that front-loads the core purpose, then parameter behavior, with no filler sentences. It is compact but the run-on structure makes it slightly harder to scan.

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?

For a six-parameter tool with no output schema, the description covers the semantically important parameters well, but the integer paging parameters (limit, offset) and result-size behavior are left entirely to the agent's inference. Adequate but with a clear gap for a tool that likely returns sizable lists.

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 only 17%, so the description must compensate, and it does: all four kind values are explained with their return characteristics, query is described as Korean/English keywords with space acting as AND, and list_categories is tied to its no-query usage. limit, offset, and category remain unclarified beyond the schema's single example for category.

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 and resource: searching the offline embedded Entry resource library, with the four kinds enumerated so an agent knows the scope precisely. It does not explicitly distinguish itself from siblings such as entry_preview_assets or entry_object_assets, which keeps it below 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 Guidelines3/5

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

Provides one concrete usage rule: call with list_categories=true and no query to retrieve the category list. Beyond that it gives no guidance on when to prefer this over sibling asset tools or on paging through large result sets, so usage is implied rather than fully specified.

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