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Glama

toolalize-mcp

list_units

List every conversion category with its units (id, symbol, name). Call this to discover the vocabulary before convert_units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It accurately describes a read operation with no side effects, and specifies the return content: categories with unit ids, symbols, and names. It does not discuss auth or rate limits, but for a simple read tool this is adequate.

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?

A single, clear sentence that is front-loaded with the primary function and ends with usage guidance. Every word adds value, no waste.

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?

Given zero parameters, no output schema, and no annotations, the description fully covers what the tool does, what it returns, and why to use it. It is complete for an agent to decide invocation.

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 input schema is empty (0 parameters), so description value is assessed on added context. The description explicitly enumerates the returned fields (id, symbol, name), adding meaning beyond the schema's emptiness.

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 lists conversion categories and their units (id, symbol, name), with a specific verb 'list' and resource. It distinguishes from the sibling 'convert_units' by noting it is for vocabulary discovery before conversion.

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 explicitly says to call this before convert_units, providing clear when-to-use guidance. It does not address convert_currency, but that is a separate domain; the guidance is sufficient for the primary sibling.

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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Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: convert_currency handles monetary conversions, convert_units handles other unit conversions, and list_units provides the vocabulary for convert_units. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (convert_currency, convert_units, list_units) in snake_case, making them predictable and easy to understand.

Tool Count5/5

Three tools is exactly right for this domain: one for listing conversions, two for performing conversions (separated by type). No extraneous or missing tools.

Completeness5/5

The tool set covers the full lifecycle of unit/currency conversion: discover available units (list_units), perform conversions for both monetary and other units. No obvious gaps.