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America/Buenos_Aires clock

weather-hint

Current temperature for a city 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

C2.7/5.0
Behavior2/5

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 reveals only that the tool fetches from Open-Meteo and returns a temperature; it does not mention units, error behavior, network dependence, rate limits, or whether the operation is read-only.

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 very terse and front-loaded, but it is not appropriately sized for a tool whose schema includes seven parameters and no annotations. It is concise to the point of under-specification rather than efficiently complete.

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 the seven-parameter schema, no annotations, and no output schema, this description is grossly incomplete. An agent cannot reliably determine required inputs, expected output format, or failure conditions from this definition 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?

The description mentions 'city', which aligns with the city param, but the input schema contains many other params (ref, url, feed, host, json, path) with no guidance about which are actually needed or ignored. With a large number of undocumented-in-description params, the description fails to compensate for the ambiguity.

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 states a specific action and resource: it returns the current temperature for a city and identifies Open-Meteo as the data source. This is clear and distinct from the sibling tools, though it does not explicitly contrast itself with any alternative weather tool.

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 description implies the usage context: use this tool when you need a city's current temperature. However, it gives no explicit guidance about when not to use it, no prerequisites, and does not mention alternatives among the sibling tools.

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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