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?
With no annotations present, the description carries the full burden of behavioral disclosure. It reveals a privacy-relevant behavior (identifiers are not retained) but remains silent on what 'classified' means, how the four parameters (url, host, json, zone) are consumed, and what the tool returns. This is a meaningful gap for a tool that appears to perform some kind of request analysis.
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 front-loaded, with no wasted sentences. The two statements are efficient. However, the brevity comes at the cost of clarity, and the phrase 'Show how this request is classified' is vague enough that conciseness does not fully serve the agent.
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?
The tool has no output schema and no annotations, so the description is the sole source of contextual information. It fails to explain what 'classified' produces, how an agent should interpret the response, or when this tool is relevant relative to its siblings. For a tool with four heterogeneous parameters, this is incomplete.
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%, so the baseline is 3; each parameter (url, host, json, zone) already has a clear description in the schema. The tool description does not add parameter-specific meaning, such as how the parameters relate to classification or whether they are alternatives or jointly required. It neither compensates for a schema gap nor adds value beyond it.
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?
The description 'Show how this request is classified' states a verb but does not specify what classification means, what kind of request, or what output the agent should expect. It is not a clear verb+resource statement and does little to distinguish the tool from its siblings, which already cover citation, URL normalization, validation, and timezone conversion.
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?
The description provides no explicit guidance on when to use this tool versus its siblings. The privacy note ('No identifiers are retained') is useful but does not help an agent choose between compatibility, citation, normalize-url, validate-json, and similar tools. No exclusions, prerequisites, or alternative conditions are mentioned.
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.
Most tools target a distinct shape or check, but `citation` and `normalize-url` both return URL host/scheme information, and `timezone`/`utc-time` overlap enough to cause occasional misselection. Overall, tool descriptions clarify the intended purpose in most cases.
All tool names are lowercase and hyphenated, which is a consistent casing convention. The mix of noun-style names like `citation` and verb-object names like `validate-json` is a minor semantic inconsistency but not a confusing one.
With 11 tools, the count is within a reasonable range for a lightweight utility server. Some reference-style helpers like `status-catalog` and `iana-zones` could be consolidated, but the set is not bloated.
The set covers URL, time, phone, JSON, and robots shape checks, but the broad 'shape' theme suggests notable gaps such as email or IP address shape validation and timezone conversion. These omissions are workable but could cause agent dead ends.