Split a hostname into labels without WHOIS or ownership data.
| 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?
The description does not disclose side effects, permissions, or data handling practices. Although the operation seems read-only, there is no explicit statement, and the parameter description for 'json' mentions 'discarded after the check,' which introduces ambiguity about side effects not covered in the main description.
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 main description is a single, concise sentence that directly conveys the operation. It has a clear subject and verb, though the phrase 'without WHOIS or ownership data' adds a slight tangential note. The structure is simple and efficient.
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 description is incomplete for practical use because the parameter definitions are contradictory and unrelated to the stated purpose. A user would be unsure which parameters to provide and how they relate to the hostname splitting, especially with irrelevant fields like 'json' and 'zone' present.
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?
The parameter descriptions are severely mismatched with the tool's purpose. 'url' is described as an 'HTTPS URL to normalize or cite,' 'json' as 'JSON text to validate,' and 'zone' as 'IANA timezone name,' all of which are irrelevant to splitting a hostname. Only 'host' (Public hostname) seems plausible, but the overall schema provides no meaningful guidance and appears to contain copy-paste errors from other tools.
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 clearly states the action ('split a hostname into labels') and the resource (hostname), and the clarification 'without WHOIS or ownership data' adds useful context. However, it is slightly vague about the output format, but the core purpose is understandable.
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 is provided on when to use this tool versus alternatives like 'normalize-url' or 'validate-json' from the sibling list. The description does not mention criteria for selection or any prerequisites, leaving the user to infer usage.
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.
Each tool has a distinct purpose (country code, URL manipulation, timezone, JSON validation, etc.) with no overlapping functionality, so there is no ambiguity in selecting the right tool.
All names use lowercase with hyphens, but the pattern is inconsistent: some are noun-only (e.g., 'cc-jp', 'iana-zones') while others are verb-noun (e.g., 'normalize-url', 'validate-json'). The style is uniform but the grammar is mixed.
With 11 tools, the count is reasonable, but the collection feels like a random assortment of utilities rather than a focused feature set, making the size slightly unjustified.
There is no coherent domain to evaluate completeness against. The tools span unrelated areas (ISO, HTTP, timezones, JSON, robots), so the set is incomplete for any single purpose and lacks a clear scope.