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Europe/Andorra 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

C2.1/5.0
Behavior1/5

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

No annotations are provided, so the description must carry the full burden. It only states the output (lat/long) and the data source (Open-Meteo) but does not disclose that it likely performs a network call, discards most input parameters (as hinted by schema descriptions), or any side effects. The behavior is entirely opaque.

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

Conciseness3/5

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

The description is a single short sentence, which is concise, but it lacks essential information. It does not front-load critical details like which parameter to use or what happens to other inputs. Being short without substance is under-specification rather than good conciseness.

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?

With 9 parameters, no annotations, and no output schema, the description is grossly incomplete. It does not explain how to specify the place, what the return format is, or any constraints. An agent cannot reliably call this tool based on the description alone.

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?

Schema coverage is 100% because each parameter has a description, but these descriptions are inconsistent with the tool's stated purpose (e.g., 'city' mentions a weather hint, others mention discarding). The tool description adds no clarification about which parameters are relevant for geocoding, leaving the agent confused about how to pass the place. It fails to add meaning beyond the schema.

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 the tool returns latitude and longitude for a place via Open-Meteo, which is a clear verb+resource. However, it does not indicate which of the 9 parameters specifies the place, and it doesn't differentiate from the sibling 'weather-hint' beyond the output type. The purpose is identifiable but input mapping is ambiguous.

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?

There is no guidance on when to use this tool versus alternatives like 'weather-hint' or other hint tools. The description does not mention any conditions, exclusions, or contexts where this tool is preferred. The agent is left to infer usage from the name alone.

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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