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 provided, the description carries the full burden of behavioral disclosure, and it fails. It does not state whether the tool validates input, returns status codes, mutates anything, or what side effects occur. The parameters suggest some input-processing behavior, but the description gives no hint of it.
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 only six words, which is under-specification rather than effective conciseness. It lacks substance and does not earn its place because it conveys almost no actionable information to an agent.
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?
For a tool with four parameters, no output schema, and no annotations, this description is severely incomplete. An agent cannot determine what the tool does, what inputs are expected, what it returns, or when to invoke it, making the definition nearly useless.
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 input schema already documents all four parameters. The description adds no meaning beyond the schema and does not explain how each parameter relates to the catalog, but baseline 3 applies because the schema covers the parameters adequately.
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 'Short catalog of common HTTP status codes' merely restates the tool name 'status-catalog' without specifying any action the tool performs. It does not explain how the four input parameters (url, host, json, zone) relate to cataloging HTTP status codes, nor does it distinguish this tool from siblings like citation or compatibility.
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 guidance is provided about when to use this tool versus its siblings. The description gives no context, prerequisites, or exclusion criteria, leaving the agent to infer the tool's purpose from the unhelpful name.
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 target a distinct shape or check, but `citation` and `normalize-url` both return URL host/scheme information, and `timezone`/`utc-time` overlap enough to cause occasional misselection. Overall, tool descriptions clarify the intended purpose in most cases.
All tool names are lowercase and hyphenated, which is a consistent casing convention. The mix of noun-style names like `citation` and verb-object names like `validate-json` is a minor semantic inconsistency but not a confusing one.
With 11 tools, the count is within a reasonable range for a lightweight utility server. Some reference-style helpers like `status-catalog` and `iana-zones` could be consolidated, but the set is not bloated.
The set covers URL, time, phone, JSON, and robots shape checks, but the broad 'shape' theme suggests notable gaps such as email or IP address shape validation and timezone conversion. These omissions are workable but could cause agent dead ends.