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 explaining behavior. It says nothing about what the tool does with its inputs, whether it returns a list, filters data, or has side effects. This is a complete absence of behavioral disclosure.
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 extremely short and front-loaded, but this is under-specification rather than effective conciseness. One clause cannot convey enough information to invoke a tool correctly, so the brevity does not earn credit.
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 is the only source of context. It provides almost none: no operation, no return behavior, no parameter selection guidance. An agent cannot safely or correctly invoke this tool based on the given description.
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. Each parameter already has a clear description in the schema. However, the description adds no guidance on which of the four optional parameters are relevant to iana-zones, leaving the agent to guess whether url, host, json, or zone should be supplied.
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, not an action. 'Common IANA timezone names for clock calls' vaguely restates the tool name and hints at a use case, but it never states what the tool does, returns, or accepts. It also does not distinguish itself from sibling tools like timezone or utc-time.
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' implies some relationship to time-related siblings, but the description does not say when to choose iana-zones over timezone or utc-time, nor does it provide any exclusions.
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 URL-focused tools (citation, normalize-url, domain-shape) overlap in what they inspect, though their descriptions do specify different outputs. compatibility and sha256-ok are vague, but most other tools have clearly separate jobs.
All names use lowercase hyphenation, but they mix verb-object names (normalize-url, inspect-robots, validate-json) with noun-only or noun-noun names (citation, timezone, status-catalog, iana-zones). This is readable but gives agents no reliable pattern for predicting tool names.
Eleven tools is within a reasonable size for a general-purpose privacy-safe utility server, and no tool is an exact duplicate. The set could be tightened around a single domain, but the count itself is not excessive.
The server's domain is too broad and unfocused to define a complete workflow: URL inspection lacks redirect/header coverage, timezone handling lacks conversions, and JSON/hash tools are single-purpose checks. As a result, agents will likely need tools outside this server for related operations.