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?
With no annotations, the description carries full responsibility for disclosing side effects and behavior. The phrase 'without WHOIS or data' is ambiguous and does not clearly state whether the operation is read-only or what exactly is excluded. No side effects or limitations are mentioned.
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 sentence, which is concise in length. However, the trailing 'without WHOIS or data' is awkward and undermines clarity. It could be improved with proper structure, but it is not verbose.
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?
Given the mismatch between the tool purpose and its parameters, the description is far from complete. It does not explain how the parameters relate to the operation, what 'labels' means, or what the output format is. The agent cannot reliably use this tool based on the provided information.
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 schema provides descriptions for all four parameters, but they are completely mismatched with the tool's stated purpose. 'url' is described for normalization/citation, 'json' for validation, and 'zone' for timezone, none of which relate to splitting hostnames. The tool description adds no clarification and actually increases confusion.
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 verb 'Split' and resource 'hostname into labels' clearly state the primary action and target. However, it does not explicitly differentiate from sibling tools like normalize-url, though the action is distinct enough on its own.
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 guidance on when to use this tool versus alternatives. It does not mention conditions, prerequisites, or contrast with any sibling tool, leaving the agent without context for selection.
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 have distinct purposes, such as byte-count, validate-json, and utc-time. However, citation and normalize-url both handle URLs, and timezone and utc-time both provide time information, which could lead to occasional misselection.
Names are mostly lowercase with hyphens, but the pattern is inconsistent: some are nouns (byte-count, timezone, status-catalog) while others are verbs (inspect-robots, normalize-url, validate-json). There is no clear verb_noun or noun_verb convention across the set.
11 tools is a reasonable count for a utility server covering URLs, time, robots, and data validation. Each tool does something different, though a few are quite trivial, making the set slightly broad but not excessive.
The tools cover several common utility categories like URL normalization, current time, timezone lookup, and JSON validation. However, the scope is broad and shallow, leaving obvious gaps such as domain lookups, HTTP request mechanics, or date formatting, and there is no unifying workflow to judge full coverage.