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Five-field cron shape

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

C2.5/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It fails to state that only the 'city' parameter is likely used, that other parameters are ignored, that a network call is made, or what the output format is. The phrase 'via Open-Meteo' hints at a service but gives no operational detail.

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 with no extraneous words, so it is concise. However, it lacks structure and front-loading—it doesn't highlight the key parameter or usage context, making it too minimal to be genuinely helpful.

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 output schema, and no annotations, the description is severely incomplete. It doesn't specify the output format, which parameter is required, how the other parameters affect behavior, or any prerequisites. An agent cannot reliably call this tool correctly based on the given information.

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% but the parameter descriptions are misleading relative to the tool's purpose. For example, 'city' is described as 'City name for a public weather hint; discarded after the call', which suggests a weather-related hint rather than geocoding. The tool description adds no clarification about which parameter maps to the place, leaving the agent confused about how to invoke it correctly.

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?

The description clearly states the tool returns latitude and longitude for a place via Open-Meteo, distinguishing it from siblings like weather-hint or timezone. However, the input schema includes many unrelated parameters (ref, url, feed, etc.) that muddy the intended purpose, leaving ambiguity about which input actually drives the geocoding.

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 is given on when to use this tool versus alternatives. The description doesn't mention that it's for geocoding city names, nor does it exclude other tools like weather-hint or timezone. The agent must infer usage from the name and vague description.

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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