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Glama

FX Convert

fx_convert
Read-onlyIdempotent

Convert an amount between two currencies at the most recent reference rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYes
to_currencyYesDestination currency code, e.g. EUR.
from_currencyYesSource currency code, e.g. USD.

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already establish that the operation is read-only, idempotent, and non-destructive, so the description does not need to restate that. It adds the useful detail that conversion uses the 'most recent reference rate' rather than a custom or historical rate, but it does not disclose output shape, rounding behavior, or rate-source limitations.

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 sentence that front-loads the action ('Convert an amount') and the key scope ('most recent reference rate'). There is no filler, redundancy, or irrelevant context.

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?

For a simple three-parameter read-only conversion with rich annotations, the description is nearly complete: it states the action, the present-time scope, and the parameters are self-evident from the schema. The only missing piece is an explicit return-shape hint since there is no output schema, though the converted amount is strongly implied by the tool's purpose.

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

Parameters2/5

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

The schema documents currency codes for from_currency and to_currency but leaves amount as just a number. The description does not fill that gap: it neither defines amount as a positive decimal in the source currency nor explains precision or minimums. It adds essentially no parameter meaning beyond what the schema already provides.

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 uses a specific verb ('Convert') and names the exact operation: an amount between two currencies, scoped to the most recent reference rate. This clearly distinguishes it from historical/timeseries fx siblings. An agent can identify what this tool does without opening sibling definitions.

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 phrase 'most recent reference rate' implies this is for current conversions rather than historical analysis. However, it never explicitly names alternatives such as fx_historical or fx_timeseries, nor does it state when not to use this tool. The agent must infer routing from sibling tool names.

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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TDQS

B3.2/5.0
Disambiguation2/5

Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.

Naming Consistency4/5

All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).

Tool Count1/5

129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.

Completeness4/5

Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.

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