Show how this request is classified. No identifiers are retained.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full disclosure burden; it offers one behavioral fact ('No identifiers are retained') but omits side effects, output format, and whether it performs external calls or validation. This is partial coverage at best.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and free of fluff, with two simple sentences, but it is too skeletal to be considered well-crafted for an AI agent. The first sentence is front-loaded yet ambiguous, and the structure does not compensate for omitted details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description must stand alone, but it provides no information on return values, classification categories, how the four optional parameters are used, or any related behavior. An agent cannot call this tool correctly based on the provided description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and each parameter has a short description, so the schema already documents the parameters. The tool description itself adds no parameter-level meaning, which keeps this at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a verb and resource ('Show how this request is classified') but does not explain what classification means or which inputs drive it; the resource is vague and not tied to the tool name 'compatibility'. It also fails to differentiate from siblings like validate-json or normalize-url.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; the description never references a use case, prerequisites, or conditions. There is no mention of the sibling tools or when the classification is relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools operate on URLs and return overlapping metadata (citation vs normalize-url vs compatibility), and timezone overlaps with tz-australia-sydney. While descriptions add detail, an agent could easily select the wrong tool for host/status or local-time tasks.
Tool names mix single nouns (citation, timezone), hyphenated noun compounds (domain-shape, status-catalog), and verb_noun commands (inspect-robots, validate-json). There is no consistent verb_noun or resource_action pattern, making the surface feel ad hoc.
Eleven tools is not inherently too many, but for a server named 'Australia/Sydney clock' the majority of tools are unrelated URL/HTTP/JSON utilities. The set would be better split into a clock server and a web-metadata server.
The time-related surface is reasonably complete with UTC, named timezone, Sydney time, and a zone catalog, but notable gaps remain such as timezone conversion and offset information. The URL/HTTP tools cover several metadata operations but lack obvious related operations, so overall domain coverage is uneven.