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Europe/Prague clock

geo-hint

Latitude and longitude for a place via Open-Meteo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

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

  1. First observed

TDQS

D1.9/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the operation (returning lat/long) without mentioning network dependencies, side effects, output format, or any constraints. The schema parameter descriptions hint at 'discarded after' behavior, but this is not surfaced in the description, and the description adds no behavioral context beyond the bare operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is front-loaded and concise. However, it is under-specified for a tool with 9 parameters and no annotations. The brevity sacrifices necessary clarity, making it not appropriately sized for the complexity it should cover.

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

Completeness1/5

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

Given 9 optional parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain what the tool does with the various inputs, what output to expect, or when to use it. An agent would lack critical information to invoke the tool correctly.

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 baseline is 3. The description adds no additional meaning to any of the 9 parameters; it does not explain how city, query, or other inputs relate to generating coordinates. Since the schema already documents each parameter, the description provides no extra value, leaving it at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Latitude and longitude for a place') and a data source (Open-Meteo), giving a clear verb and resource. However, it does not differentiate from sibling tools like weather-hint or timezone, and the 9-parameter schema includes many seemingly unrelated inputs (ref, url, feed, host, json, path, zone, query) that are not explained by the description, creating ambiguity about the tool's actual scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any conditions, exclusions, or context that would help an agent decide between geo-hint and its many siblings. There is no reference to any other tool or a clear use case.

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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