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Glama

Common zone count

by io.github.sadri-dridi
OverviewAdmin

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. Changed5 schema fields changed
    • addedInput schema / properties / city
      Added value: +{
+  "description": "City name for a public weather hint; discarded after the call",
+  "type": "string"
+}
    • addedInput schema / properties / feed
      Added value: +{
+  "description": "Public RSS or Atom URL; titles discarded",
+  "type": "string"
+}
    • addedInput schema / properties / path
      Added value: +{
+  "description": "File path to check; no disk access",
+  "type": "string"
+}
    • addedInput schema / properties / query
      Added value: +{
+  "description": "Search text; discarded after the length check",
+  "type": "string"
+}
    • addedInput schema / properties / ref
      Added value: +{
+  "description": "Git ref name; discarded after the shape check",
+  "type": "string"
+}
  2. First observed

TDQS

C2.2/5.0
Behavior2/5

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

The description contributes one useful behavioral fact: 'No identifiers are retained.' However, with no annotations at all, it fails to disclose whether this operation has side effects, whether any input is persisted or transmitted, what processing is performed, or what the response contains.

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 brief and the privacy note is useful, but the brevity is not backed by structure or front-loaded detail that would help an agent understand the tool. It reads more as under-specification than as disciplined conciseness.

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?

With four optional parameters, no output schema, no annotations, and a highly vague name, the description is fundamentally inadequate. An agent cannot determine which input(s) to provide, what classification will be returned, or how this relates to the sibling tools, making correct invocation essentially guesswork.

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?

The schema describes all four parameters fully, so schema coverage is 100% and the baseline is 3. The description itself adds no parameter-level meaning, leaving it unclear which parameter(s) the classification operates on.

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?

'Show how this request is classified' conveys a verb and a vague resource, but the description never says what 'request' refers to, how it is classified, or what classification means. It does not meaningfully differentiate this tool from siblings like normalize-url, validate-json, or citation.

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 about when to use this tool instead of an alternative, no mention of which inputs are appropriate, and no exclusions or prerequisites. The agent is left to infer usage from the tool 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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