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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

C2.8/5.0
Behavior3/5

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

The description does disclose a meaningful behavioral trait: 'No identifiers are retained.' With no annotations available, this privacy/disposal cue carries real value, but it does not address side effects, auth, network behavior, or what classified output the caller should expect.

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 two short, front-loaded sentences with no filler, and the privacy sentence adds distinct value. It is concise as written, but the first sentence is too vague for the tool's apparent complexity.

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?

With 9 heterogeneous optional parameters, no output schema, and no annotations, the description leaves serious gaps: an agent cannot know whether to provide all inputs, only one, or what the returned classification will look like. The schema gives good per-parameter information, but the overall behavior and input grouping remain undefined.

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?

Every parameter has full schema-level descriptions, so the baseline is 3 even though the free-text description adds no per-parameter meaning. It does not explain how the various optional inputs relate to one classification or which should be used together.

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 says an action ('show how classified') and a resource ('this request'), which is enough to see that this is some kind of classifier, but it never says what classification is produced or what criteria are used. It is vague about purpose and does not distinguish it from the many shape-checking and normalization siblings.

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 a sibling such as validate-json, normalize-url, domain-shape, file-path-ok, or git ref checkers. No when-to-use, when-not-to-use, or alternative-selection hint is provided.

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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