Skip to main content
Glama
Galaxy Cluster Catalogs MCP Server

Galaxy Cluster Catalogs MCP Server

list_clusters_skills

Lists this server's named multi-tool recipes so you can find the right skill for a task, then load it to get the tool chain, parameters, and checks to follow.

Instructions

List this server's skills: named multi-tool recipes.

A skill is procedural know-how - which tools to chain, in which order,
with what parameters, and how to sanity-check and report. When a task
matches one, load it with the load-skill tool and follow it.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_clusters_skills"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
filesYes
statusYes
messageYes
metadataYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description must carry behavioral disclosure. The verb "List" and the explanation of skills imply a read-only discovery operation, but the description does not explicitly state read-only behavior, whether all skills are returned, or any access constraints.

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 front-loaded with the core action ("List this server's skills: named multi-tool recipes") and follows with a concise definition and next-step guidance. The sentence defining procedural know-how is slightly long but earns its place by clarifying what a skill contains.

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?

The output schema already covers return values, and the zero-parameter schema needs no parameter explanation. The description explains what skills are and points to load-skill for execution, though it does not mention pagination or exhaustiveness, which is a minor gap for a simple listing tool.

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?

This tool has zero parameters, so parameter semantics are minimal by design. Per the rubric, zero parameters establishes a baseline of 4, and the description does not need to compensate for missing parameter documentation.

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 states a specific verb and resource: "List this server's skills: named multi-tool recipes." It defines what a skill is, which distinguishes the resource from dataset-listing siblings like list_clusters_datasets. It names the load-skill tool as the follow-up, though it does not explicitly contrast with other listing siblings.

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?

The description implies usage by saying to load a skill with load-skill when a task matches one, but it does not explicitly say when to call list_clusters_skills itself versus list_clusters_datasets or describe_clusters_dataset. There are no when-not guidelines or explicit alternatives for discovery.

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