Fetch a public robots.txt and return group counts only.
| 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 behavioral burden. It does disclose that the fetch is of a public resources and that the output is limited to group counts, but it omits behavioral details such as redirect handling, missing robots.txt behavior, error conditions, or 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 a single front-loaded sentence with no filler. It states the action, resource, and output in an efficiently scannable way.
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 four unrelated-looking parameters, no required fields, no output schema, and no annotations, the description is too thin to fully guide invocation. An agent cannot infer which parameters are relevant or what the 'group counts' output will look like.
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 even though the tool description adds no parameter-specific meaning. The schema already documents each parameter clearly, but the description does not clarify how url, host, json, or zone relate to fetching robots.txt.
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 names a specific verb ('Fetch'), a precise resource ('a public robots.txt'), and a clear result ('return group counts only'). It is not a tautology and can be distinguished from siblings like normalize-url, citation, and domain-shape.
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?
The description gives no guidance about when to use this tool versus alternatives, nor when not to use it. There are no references to sibling tools or conditions that would route an agent toward inspect-robots instead of another URL-related tool.
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, especially citation, normalize-url, and domain-shape, all of which inspect URLs or hostnames. The time-related tools utc-time and year-utc also overlap because a timestamp contains the year. Other tools are more distinct, but the boundary between these clusters is not always clear.
All names use lowercase kebab-case, which gives some visual consistency. However, the pattern is mixed: some are verb-object names (normalize-url, validate-json, inspect-robots), while others are standalone nouns or noun-noun compounds (citation, timezone, status-catalog, year-utc). This makes the naming readable but not predictably consistent.
Eleven tools is a reasonable number for a utility-style server, neither too sparse nor overwhelming. The count feels slightly inflated by the mixed domains, but no individual tool is redundant enough to cut. Overall, the count is appropriate for a general-purpose utilities server.
The set covers a few small domains—URL inspection, time/timezone, HTTP status, and JSON validation—but none are fully fleshed out. For example, there is no timezone conversion or date formatting tool, and URL tools lack any operation for actual page retrieval. While the tools are self-contained, the overall surface feels more like a collection of samples than a complete workflow.