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JSON Lines row count, body discarded

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?

There are no annotations, so the description carries the full transparency burden. It does disclose that an external provider (Open-Meteo) is used and that the output is a temperature, but it omits network/rate-limit/failure behavior and doesn't reveal that many parameters are discarded after a check (per the schema). The description also doesn't clarify the tool's actual 'hint' nature versus returning authoritative meterological data.

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 seven-word sentence with no filler, front-loaded with the key fact ('current temperature'). It's appropriately terse under the conciseness dimension, even though that brevity creates gaps in other dimensions.

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?

For a tool with nine optional parameters and no annotations or output schema, the description is incomplete. It covers only one parameter (city), doesn't explain what happens when multiple/all parameters are provided, and doesn't give the return shape beyond the bare word 'temperature'. An agent cannot reliably invoke the tool in all its supported modes.

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 baseline is 3. The description adds value for 'city' by linking it to an Open-Meteo temperature lookup, but says nothing about the other eight parameters (ref, url, feed, host, json, path, zone, query) that are fully described in the schema.

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 statement identifies a specific resource ('current temperature') and a specific provider ('Open-Meteo'), and the subject is clearly a city. None of the 29 siblings claim weather functionality, so an agent could pick this tool for a weather forecast request. However, it describes only one behavior for a schema with nine optional parameters and doesn't mention any hint of the 'hint' semantics the name implies.

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 when-to-use vs. when-not-to-use guidance is given. The description doesn't name an alternative (e.g., geo-hint or fetch-status), doesn't say when to use the other eight parameters, and doesn't specify any exclusion conditions. An agent would have to infer the full decision from the name and schema 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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