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 present, and the description does not disclose any behavioral side effects, inputs, or outputs. It is unclear what the tool actually does with the provided parameters (url, host, json, timezone), and whether it has any side effects.
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, but it is not effective. It lacks essential information and the single sentence is unclear. Conciseness is not beneficial when it omits critical details needed to understand the tool.
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 sibling tools (e.g., normalize-url, validate-json), the description does not explain how this tool fits into the broader context. There is no output schema or further details, leaving the tool's functionality and relationship to the parameters completely unclear.
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 parameters (url, host, json, timezone) are not explained in the description. Their names are generic and the description does not map them to the stated action of splitting a hostname into labels. The schema provides no additional context beyond field names.
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 'Split a hostname into labels without WHOIS or data' is vague and confusing. It does not clearly state the tool's purpose, and the mention of 'without WHOIS or data' is ambiguous. It fails to distinguish this tool from siblings like normalize-url or validate-json.
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. The description does not mention any use cases, prerequisites, or context where this tool would be preferred.
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 function: URL analysis, JSON inspection, time/timezone, and HTTP status. Only 'compatibility' is vaguely defined and could conceptually overlap with status-catalog, but the other descriptions prevent significant misselection.
Names mix noun-only (citation, compatibility), noun-noun (json-bytes, status-catalog), and verb-noun (inspect-robots, normalize-url, validate-json) styles with no clear pattern. All are readable, but the convention is not systematic or predictable.
With 11 tools, the count sits comfortably in the ideal range. Each tool has a specific purpose, and the set does not feel bloated, even though the overall scope spans multiple utility domains.
URL, JSON, time, and HTTP status areas each have reasonable coverage with no obvious dead ends. However, the lack of a clearly stated central domain makes completeness hard to fully evaluate, and 'compatibility' feels under-specified.