Short catalog of common HTTP status codes.
| 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 must disclose behavior, but it only says 'short catalog,' which implies a read-only lookup. It does not explain how the four input parameters affect the catalog, whether they are required, or what output is returned, leaving critical behavioral gaps.
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 fluff, which is good, but it is under-specified and reads as a fragment rather than an actionable tool definition. It is concise but not appropriately sized for a tool with four parameters and no other documentation.
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?
The tool has four optional parameters, no output schema, and no annotations, yet the description provides only a single clause. It omits return format, how to invoke the catalog, what 'common' includes, and the relationship between the parameters and the catalog, making it far from complete.
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?
Although schema description coverage is 100%, the parameter meanings are disconnected from the stated purpose: url is for normalizing/citing, json is for validation, and zone is for timezone names. The description adds no explanation of why these are relevant to a status-code catalog, so the high schema coverage does not actually help an agent call the tool correctly.
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 actionable verb+resource statement. It barely expands the tool name, and the input schema—url, host, json, zone—has no obvious connection to a catalog of HTTP status codes, making the purpose confusing.
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, what conditions favor it, or how it relates to the ten sibling tools. The description offers no context that would help an agent choose between status-catalog and tools like validate-json, normalize-url, or 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 in purpose: citation, normalize-url, and domain-shape all analyze URLs/hostnames, while iana-zones, timezone, and utc-time all relate to time. compatibility is vague and could be confused with citation or status-catalog. Only a few tools have truly distinct, non-overlapping functions.
All names use lowercase hyphenation, which is a consistent visual style. However, the pattern is inconsistent: some are imperative verbs (normalize-url, inspect-robots, validate-json) while others are noun phrases (citation, compatibility, timezone, status-catalog). The names are readable but do not follow a predictable verb_noun convention.
Eleven tools is a reasonable count for a utility server and falls within the typical well-scoped range. Some tools feel trivial or overlapping, such as lang-it and the multiple time-related tools, but the total is not excessive.
The tool set has no coherent unifying domain: it mixes URL parsing, HTTP status, time, JSON validation, robots.txt, and a language tag. Obvious operations like URL validation, timezone conversion, or HTTP status details are missing, and the grab-bag nature makes it impossible to assess complete lifecycle coverage.