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io.github.WiliamRosa/cosmos-semantic

io.github.WiliamRosa/cosmos-semantic

by WiliamRosa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_members

Lists available metrics, dimensions, and business rules so you can discover governed business concepts before requesting calculations.

Instructions

List the available metrics, dimensions and business rules.

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_members"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and delivers almost nothing: no indication of read-only semantics, result size, pagination, or whether the catalog is scoped by permissions or connection. The output schema offsets some of this by defining return values, but the description itself adds no behavioral context.

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 front-loaded sentence with no filler. It is arguably too terse for a no-annotation tool, but nothing in it is wasted or buried.

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 zero-parameter read tool with an output schema, the description's main job is explaining what the catalog contains, which it does. However, with no annotations at all, an agent still lacks any statement of read-safety, result scale, or how the listed members feed into query/explain.

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?

The tool takes zero parameters, so there is no parameter meaning for the description to add. Baseline of 4 applies; the sentence instead usefully expands the domain of what 'members' means.

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 ('List') and clarifies what the ambiguous tool name 'members' actually contains: metrics, dimensions and business rules. That disambiguation is genuinely useful, but it does not differentiate this tool from siblings such as search_concepts, which plausibly exposes similar catalog data.

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?

No guidance on when to use this rather than search_concepts, query, or explain. The agent must infer that this is a discovery/enumeration step before querying, and nothing states whether results should be cached or how they relate to the other tools.

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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