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?
Without annotations, the description carries the burden of explaining behavior. It does state that it fetches a public resource and returns only group counts, which is transparent. However, it does not disclose potential network errors, rate limits, or the fact that the parameter descriptions are inconsistent with the tool's purpose, which confuses rather than clarifies.
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 concise (one sentence) and front-loaded with the primary action. However, it lacks a clear structure to separate purpose, parameters, and output. The brevity leaves out essential details that would make it well-formed.
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 description and schema together are incomplete and contradictory. There is no output schema, no indication of which parameters are required, and no explanation of how the parameters relate to the tool's function. An agent would be unable to correctly invoke this tool based on the provided information.
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 lists four string parameters, but their descriptions are mismatched: 'url' is 'HTTPS URL to normalize or cite', 'json' is 'JSON text to validate', and 'zone' is 'IANA timezone name'. None of these align with the stated purpose of fetching robots.txt. The tool likely only needs a URL or host, but the schema and descriptions do not convey this, making parameter usage unclear and misleading.
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 states a specific verb ('Fetch') and resource ('public robots.txt') and clarifies the output ('return group counts only'). It is distinct from sibling tools like 'normalize-url' or 'validate-json', though it could be more explicit about its intended use case.
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 provides no guidance on when to use this tool versus alternatives. It does not mention that this is for checking robots.txt rules or that it is preferable to other tools for this purpose. No context is given for selecting it.
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 clearly distinct outputs: URL metadata, URL normalization, hostname labels, robots inspection, HTTP status catalog, time lookups, JSON validation, and hex encoding. The main ambiguity is between citation and normalize-url, which both return host/scheme information, and between timezone and utc-time, though the descriptions help clarify their different outputs.
All names use lowercase hyphenation, giving a surface-level consistency. However, the set mixes nouns like citation and timezone, verb-object forms like inspect-robots and normalize-url, and the unusual hex-ok, so there is no consistent naming pattern.
With 11 tools, the count is reasonable and within the well-scoped range. The tools span URL, time, and data utility categories without feeling redundant, though the breadth suggests a general-purpose utility server rather than a tightly focused one.
The set covers common URL, time, and simple data-validation needs, but the overall domain is broad and somewhat unclear. Obvious companion operations are missing, such as hex decoding, timezone conversion, or more detailed request inspection beyond the vague compatibility tool.