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?
No annotations are provided, so the description carries the full burden. It does disclose a limitation ('without WHOIS or ownership data'), but it omits behavioral details such as return format, whether any network calls occur, or how invalid inputs are handled.
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 a single, front-loaded sentence with no wasted words. However, it is under-specified for a tool with four parameters and no annotations, so it is concise but not appropriately sized for the tool's complexity.
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 four optional parameters, no required parameters, no output schema, and no annotations. The description only covers hostname splitting and fails to mention the other three parameters, output behavior, or how the tool should be invoked. This is inadequate for reliable agent selection and use.
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. The description adds minimal meaning beyond the schema — it loosely connects to the 'host' parameter but does not explain how 'url', 'json', or 'zone' relate to splitting a hostname. With full schema coverage, this is acceptable but not enhanced.
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 states a specific operation: 'Split a hostname into labels' — a clear verb plus resource. The qualifier 'without WHOIS or ownership data' helps position the tool against other domain-lookup tools, though no sibling tools are actually listed to compare against.
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?
There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, typical use cases, or exclusions, leaving the agent to infer when splitting a hostname is appropriate.
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 overlap around URL inspection (citation vs normalize-url) and time (timezone vs utc-time), though their descriptions clarify differing outputs. The vague compatibility tool adds some ambiguity about when it should be selected.
All names are lowercase and hyphenated, which is a consistent style, but the pattern mixes noun phrases like citation and timezone with verb-led names like normalize-url and validate-json. This is readable but does not follow one predictable convention.
Eleven tools is a reasonable size for this collection of privacy-preserving utility functions. The count is not bloated, though the time-related tools could arguably be consolidated.
The tool surface covers the apparent domain of inspecting data shapes without retaining content: URLs, email, JSON, robots.txt, time, and HTTP status. Minor gaps like direct header or DNS inspection exist, but common workflows are not dead-ended.