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TOML table count, body discarded

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 provided, the description carries the full burden of disclosing behavior. It only states the core function (lat/lon lookup) but fails to mention that most parameters are discarded, that the tool performs a network call to Open-Meteo, or that it has any side effects or error conditions. The description also does not explain the odd schema where many parameters appear irrelevant to geo-lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no fluff. It is front-loaded with the core function. However, given the complexity of the schema (9 parameters), the extreme brevity borders on under-specification rather than efficient conciseness. Still, it earns a 4 for having no wasted words.

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?

The tool has 9 parameters, no output schema, and no annotations, yet the description provides only a one-line purpose. It does not explain which parameter to use, what the return format is, how errors are handled, or why the other parameters exist. An agent cannot reliably invoke this tool correctly based on this description alone, making it seriously incomplete.

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 documents all 9 parameters. The tool description adds no additional meaning beyond the schema, so the baseline of 3 is appropriate. However, the schema descriptions themselves are confusing (e.g., 'discarded after the shape check' for 'ref'), and the description does not clarify which parameter is the primary input (likely 'city'). Thus, the description adds no value over the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: obtaining latitude and longitude for a place via Open-Meteo. However, it does not specify which of the 9 parameters corresponds to the 'place', nor does it distinguish itself from sibling tools like 'weather-hint' that might also take a city. The purpose is technically present but vague given the large, seemingly unrelated parameter set.

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 guidance on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or recommended contexts. Given many sibling tools like 'weather-hint', 'iana-zones', or 'normalize-url', the lack of usage direction leaves the agent guessing about which tool to invoke for a given task.

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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