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?
There are no annotations, so the description must fully disclose behavioral traits on its own. It only hints that this provides names for clock calls and does not mention whether it returns a list, accepts input, performs a lookup, or 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 and free of filler, but it is under-specified rather than concisely complete. It spends its single sentence restating the tool name and leaves out essential operational context.
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?
With no annotations and no output schema, the description should explain what the tool returns and how parameters relate to behavior. It does neither, and the presence of four unrelated-looking parameters makes the lack of context more damaging.
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 all four parameters (`url`, `host`, `json`, `zone`) already have descriptive text. The tool description itself adds no additional meaning to the parameters, 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 'Common IANA timezone names for clock calls' is essentially a restatement of the tool name and includes no verb or explicit action. It adds only a vague hint that the tool relates to clock calls but does not clarify whether it lists, filters, resolves, or validates timezone names.
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 usage guidance is provided. The description does not say when to call this tool instead of sibling tools like `timezone`, `utc-time`, or `normalize-url`, nor does it explain what scenario requires `iana-zones`.
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: citation and normalize-url both return URL origin/host information, while timezone and utc-time both provide current time. The descriptions help separate most tools, but compatibility is vague and could be confused with classification or request-checking tools.
Names use lowercase hyphenation and are generally readable, but they mix verb-led forms like inspect-robots, normalize-url, and validate-json with noun-led forms like domain-shape, status-catalog, and utc-time. There is no consistent verb_noun or noun_verb convention across the set.
11 tools is a reasonable count, but for a server named 'Nano ID shape check' the scope feels diffuse, with URL, time, JSON, and HTTP status utilities included. Several tools do not clearly earn their place under that stated purpose.
The server claims a narrow Nano ID focus, yet only one tool directly supports it, while URL, JSON, time, and robots checks are shallow one-offs. There are no tools for generating or custom-validating Nano IDs, and URL handling stops at normalization without redirects or deeper request inspection.