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datagokr

datagokr

by datagokr-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Read-only

Inspects dataset metadata including title, organization, columns, and access details to guide subsequent data retrieval.

Instructions

검색한 데이터셋의 구조·사용법을 확인합니다. Inspect dataset metadata before use. 반환 / Returns: title, org_nm, access_kind, columns, operations, examples, page_url. dataset_id는 검색 결과의 id입니다. Use the id from search; use get for actual rows.

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": {
      "dataset_id": "<dataset_id>"
    },
    "name": "show"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataset_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

The readOnlyHint annotation is consistent with the description, which describes an inspection operation. The description adds value by enumerating the returned metadata fields and clarifying that it does not return row data (implied by 'use get for actual rows'). This goes beyond the annotation by specifying what the tool returns and what it deliberately omits.

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, with three sentences that lead with the purpose, then the return list, then the parameter guidance. There is no redundant wording, and the bilingual format does not obscure clarity. It is appropriately front-loaded and every sentence adds information.

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?

For a simple metadata-inspection tool with one parameter and an output schema, the description covers the essential usage context: what it does, what it returns, where the id comes from, and how it relates to 'get'. There are no gaps that would prevent an agent from calling it correctly.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining that dataset_id is the id from search results. This gives the agent both the source and the meaning of the parameter, which the schema alone does not provide. For a single-parameter tool, this is complete.

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 the tool inspects dataset metadata and lists the exact return fields (title, org_nm, access_kind, etc.). It explicitly contrasts with 'get' for actual rows, distinguishing it from a key sibling. The verb 'inspect' and resource 'dataset metadata' are specific and unambiguous.

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 advises to inspect metadata before use and explicitly says to use 'get' for actual rows, providing clear routing between two tools. It also instructs to use the dataset_id from search results. However, it does not mention other siblings like fields, preview, or fetch, so guidance is partial but sufficient for the primary alternative.

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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