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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does state that the tool fetches a public robots.txt and returns only group counts, which reveals the core behavior and output shape. However, it omits details like whether the URL/host must be public, how malformed inputs are handled, or any side effects beyond the fetch.
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 nine-word sentence that is front-loaded with the action and immediately narrows the output with 'group counts only.' Every word earns its place; there is no filler or redundancy.
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 no annotations and no output schema, and its four optional parameters are described in ways that conflict with the stated purpose. The description defines neither the return structure of 'group counts' nor how parameters map to the request. An agent would likely struggle to invoke this tool correctly without additional context.
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, but the description adds no parameter guidance and the schema descriptions are actively misleading in this context: 'url' is described as 'HTTPS URL to normalize or cite,' 'json' as 'JSON text to validate,' and 'zone' as 'IANA timezone name.' This leaves the agent unable to determine which parameter identifies the target robots.txt. The description does not compensate for this mismatch.
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 specific and concise statement: 'Fetch a public robots.txt and return group counts only.' It identifies a clear verb, resource, and an output restriction, and it is topically distinct from siblings like validate-json or citation. However, it does not explicitly name or exclude sibling tools, and the input schema's unrelated parameter descriptions slightly muddy the intended scope.
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 prefer this tool over alternatives, nor does it specify which of the four optional parameters should be provided to fetch a robots.txt file. An agent is left to infer usage solely from the tool name and one-sentence description, with no exclusions or context.
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 the URL/host/status space: citation, normalize-url, and domain-shape all return host-like information, and compatibility is vague. The descriptions help separate them, but an agent could still misselect when looking for a specific URL metric.
Names mix single-word nouns like citation and timezone, noun phrases like domain-shape and status-catalog, and verb-led names like normalize-url and validate-json. All use kebab-case, but there is no consistent verb/noun pattern across the set.
Eleven tools is within a reasonable range for a utility server. Most tools have narrow, distinct purposes, though a few time-related and URL-related tools feel somewhat redundant.
The set covers URL normalization, JSON/JWT inspection, robots, HTTP status, and time utilities, but the lack of a single cohesive domain leaves noticeable gaps. For example, there is no generic URL validation, no HTTP header inspection, and the compatibility tool is underspecified.