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Pacific/Tongatapu 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

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the data source (Open-Meteo) but does not disclose that the temperature is a 'hint' for a city, that inputs other than city are discarded, or any caching/error/response characteristics. The schema's discard notes are not referenced in the description.

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, focused sentence that states the tool's purpose and data source with no filler. It is appropriately front-loaded and easy to scan. Nothing extraneous is included.

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

Completeness2/5

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

Given the complexity of the input schema (many parameters, even if discarded) and the absence of an output schema, the description is too sparse. It fails to mention return format, error behavior, or that only 'city' is used. An agent would not know whether the other parameters affect the call or what to expect in the response.

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?

The input schema provides descriptions for all parameters (100% coverage), including clarity that non-city params are discarded. The description adds no parameter-specific meaning beyond mentioning 'city' indirectly. Baseline of 3 is appropriate since the schema handles the heavy lifting.

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 the current temperature for a city using Open-Meteo. It distinguishes it from the sibling tools, none of which cover weather. However, it uses a noun phrase rather than an explicit verb like 'get', and could more clearly state the action taken.

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?

The description provides no guidance on when to use this tool versus alternatives, any prerequisites, or exclusions. There is no mention of when not to use it or how it differs from geo-hint or timezone tools. The agent must infer usage solely from the name and 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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