Common IANA timezone names for clock calls.
| 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 of behavioral disclosure. It says nothing about side effects, return values, whether the operation is read-only, or how it uses the four schema parameters. An agent cannot tell if calling this tool returns a list of timezone names or validates a supplied zone.
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 under-specified, which is not the same as being usefully concise. The six-word noun phrase contributes no actionable behavior beyond what the tool name already implies, so it does not earn its place as a meaningful definition.
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?
Although the input schema is well-documented, the tool-level description is incomplete: there is no output schema, no annotations, and no explanation of expected return shape, default behavior with zero parameters, or relationship to sibling tools. An agent is left guessing how to call iana-zones correctly.
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%, and each parameter (url, host, json, zone) already has a clear explanation. The tool description adds no parameter-level meaning and does not explain how these parameters relate to 'IANA timezone names,' so the baseline score of 3 applies.
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 is a noun phrase that restates the tool name: 'Common IANA timezone names' is essentially an expansion of 'iana-zones.' It lacks a verb, so it does not say whether the tool lists, returns, validates, or normalizes timezone names. The added context 'for clock calls' is too weak to distinguish this from sibling tools like timezone or validate.
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 phrase 'for clock calls' hints at a use case, but it does not say what input to provide, what conditions justify calling it, or which sibling tools should be preferred instead.
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.
json-ok and validate-json are effectively duplicate JSON validity checks, and several URL/HTTP tools (citation, normalize-url, domain-shape) have overlapping hostname/status concerns. compatibility is too vague to distinguish reliably from the other HTTP-related tools.
The names are all lowercase hyphenated, but they mix noun phrases (citation, timezone), imperative verbs (normalize-url, validate-json), and adjective constructions (json-ok). There is no consistent verb_noun or resource_action pattern, and the same JSON operation is called two different names.
Eleven tools is not inherently too large, but the set is not tightly scoped to the apparent 'JSON validity' purpose and bundles URL, robots, HTTP, and time utilities. The duplicate JSON validation tools also make the count feel padded rather than earning their places.
There are useful clusters for URL inspection, HTTP status, time, and JSON validity, but no clear workflow connects them and compatibility remains unexplained. Within a broad safe-web/utility interpretation the basics are present, yet obvious helpers such as header inspection or a single unified JSON validator are missing.