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Asia/Tashkent 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

C2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'No identifiers are retained,' which is a privacy note but doesn't describe what the tool does operationally, whether it's read-only, what side effects exist, or what output format to expect. For a tool with such a broad input surface, this is insufficient.

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

Conciseness3/5

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

The description is concise (two short sentences) with no wasted words, but it's under-specified. The lack of structure or elaboration means the conciseness works against usability. It doesn't front-load any actionable information, so the brevity is not an asset 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?

This is a complex tool with 9 optional parameters, no required fields, no output schema, and no annotations. The description provides almost no context: it doesn't explain what classification is performed, how parameters are used, what results look like, or when to call it. An agent would be completely lost trying to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the parameter descriptions themselves are cryptic (e.g., 'discarded after the shape check') and don't tie to the tool's purpose of 'classification.' The description adds no meaning beyond the schema, and the schema's own descriptions don't clarify how the parameters relate to each other or to the output. The tool description fails to provide any unifying semantic context.

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 'Show how this request is classified' is vague. It identifies an action (show classification) but doesn't specify what resource is being classified, what classification means, or how it differs from the many sibling tools like validate-json or browser-url-ok. It lacks a clear verb-object structure tied to a specific purpose.

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 doesn't mention any prerequisites, exclusions, or context that would help an agent decide to invoke it. With 9 optional parameters and no required ones, it's unclear 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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