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Pacific/Efate clock

compatibility

Show how this request is classified. No identifiers are retained.

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

D1.7/5.0
Behavior1/5

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

With no annotations, the description carries the full burden. The only behavioral disclosure is 'No identifiers are retained,' which is a privacy note but reveals nothing about side effects, network access, file reads, or what happens to inputs beyond that. It doesn't say whether the tool is read-only, performs validation, or modifies state. For a tool with 9 optional parameters and diverse inputs, this is severely lacking.

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

Conciseness2/5

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

The description is a single sentence, which is technically concise, but it is under-specified rather than succinct. It omits essential information and doesn't front-load a clear purpose. Conciseness without substance is not a virtue here.

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. The description does not explain the return format, what classification means, what the tool computes, or how it handles different parameter combinations. This is a complex tool, and the description is completely inadequate for an agent to invoke it correctly.

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 each parameter has some inline description (e.g., 'Git ref name; discarded after the shape check'). The tool description adds no additional meaning about how parameters relate to the classification outcome. Since the schema already documents parameters, a baseline of 3 is appropriate, but the description fails to explain how parameters contribute to the tool's purpose.

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

Purpose2/5

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

The description says 'Show how this request is classified' – it names a verb and a resource, but 'classified' is ambiguous and doesn't specify what kind of classification or what the tool actually does. It doesn't distinguish itself from siblings like domain-shape or validate-json, which have clear purposes. The phrase is almost a placeholder for a specific capability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is zero guidance on when to use this tool versus the many sibling tools that perform specific checks (browser-url-ok, calc-eval, etc.). The description provides no context, no examples, and no exclusion criteria. An agent cannot infer when this tool is appropriate.

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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