Galaxy Cluster Catalogs MCP Server

describe_clusters_dataset

Retrieve complete details for a named galaxy-cluster dataset—products, units, conventions, URLs, and citation—to support correct data use and attribution.

Instructions

Full description of one dataset: products, units, conventions, URLs, citation.

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": {
      "name": "<name>"
    },
    "name": "describe_clusters_dataset"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	Dataset key from the list tool.

Output Schema

Name	Required	Description	Default
`files`	Yes
`status`	Yes
`message`	Yes
`metadata`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the behavioral burden. It discloses the returned content categories such as products, units, conventions, URLs, and citation, but does not discuss read-only behavior or error conditions.

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 single sentence is front-loaded and compact, listing the description contents after a clear lead phrase. There is no redundant wording.

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

Completeness4/5

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

With an output schema present and a fully documented single parameter, the description need not explain return formatting or parameter details. It is nearly complete for a simple one-dataset description tool, though it could say more about when to use it.

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?

Schema description coverage is 100%, so the input schema already defines the name parameter as a dataset key from the list tool. The description adds little beyond 'one dataset' and therefore meets the baseline for schema-covered parameters.

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 gives a clear verb and resource: it produces a full description of one dataset and enumerates the kinds of information returned. It does not explicitly name a sibling alternative, but the singular dataset scope is clear.

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?

Usage is implied by the phrase 'one dataset' and the schema note that the name comes from the list tool, suggesting it should be called after listing datasets. It does not explicitly state when to choose this over related catalog or column-description tools.

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