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 carries the full burden of behavioral disclosure. 'Short catalog' only implies a passive reference read; it does not state whether the supplied url, host, json, or zone values are used, ignored, or discarded, nor what the response contains. The description is not contradictory, but it is behaviorally thin.
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 contains no filler, which is a point in its favor. But it is so underspecified that it reads more like a label than a functional definition, and the brevity comes at the cost of missing operation and parameter guidance.
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 no output schema, no annotations, four optional parameters, and a schema that appears mismatched with the description, this is not enough for an agent to invoke the tool confidently. It does not explain how to use the inputs, what the output looks like, or whether the parameters are actually meaningful.
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 schema has 100% description coverage, so the baseline is 3 even without parameter details in the description. Each parameter has its own description. However, the description adds nothing to explain why a URL, hostname, JSON text, or timezone would be relevant to a catalog of HTTP status codes.
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 essentially a noun-phrase restatement of the tool name: a catalog of status codes. It never states an operation such as 'returns', 'lists', or 'looks up', and it fails to connect the four unrelated input properties to the stated purpose. It identifies a domain but not what an agent should expect when invoking the tool.
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 any of the siblings. No alternatives, exclusions, or context are provided, so an agent cannot determine why status-catalog would be preferred over 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.
Most tools have distinct outputs, but the URL-related tools (citation, normalize-url, domain-shape) and time-related tools (utc-time, timezone, iana-zones) form overlapping clusters that an agent could misselect. Descriptions clarify the differences, but the boundaries are not immediately obvious.
All names use lowercase hyphenation, but the set mixes imperative verb_noun names (inspect-robots, normalize-url, validate-json) with noun/adjective names (citation, compatibility, timezone, base64-ok). This is readable but not a consistent naming pattern.
Eleven tools is a reasonable size for a general-purpose utility server and none seem redundant enough to cut. A few could be consolidated, such as timezone and utc-time, but the count is not excessive.
The server covers several utility categories, including URL analysis, time, JSON validation, HTTP status, and base64, but has noticeable gaps such as no base64 decode, no timezone conversion, and no URL encoding/decoding. These missing operations limit what an agent can accomplish without another server.