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Currency SAR

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, but it only states the data source and implies a read-only weather lookup. It does not disclose output units, error behavior, external network dependency, rate limits, or the fact that the input is discarded after the call.

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?

The description is a single short sentence with no filler and the key information is front-loaded. It is concise and easy to parse, though the brevity contributes to completeness problems rather than conciseness problems.

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?

The 9-parameter schema is highly confusing for a weather tool, with many unrelated parameters and no guidance on which one to supply. There is no output schema and no annotations, so the one-sentence description leaves an agent without enough context to reliably invoke the tool among 27 siblings.

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 schema already explains each parameter, earning a baseline of 3. The description adds no real semantic value beyond reinforcing that 'city' is the relevant parameter for weather, and it does not explain why the other eight parameters are present.

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 indicates the tool provides 'Current temperature for a city via Open-Meteo,' which identifies the domain and resource. It lacks an explicit verb like 'get' or 'fetch,' but the intent is obvious and it is distinguishable from sibling tools such as geo-hint or utc-time.

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 when-to-use or when-not-to-use guidance, and no alternatives are mentioned. The only contextual detail is the data source 'Open-Meteo,' which does not help an agent decide between this tool and related hints. It is not misleading, but it provides virtually no usage direction.

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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