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, the description carries the behavioral disclosure burden. It adds useful context by noting the resource is public and that only group counts are returned, but it does not explain error behavior, what group counts mean, or how the fetch is performed. Some transparency is present, but significant gaps remain.
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 sentence with a clear active verb, explicit resource, and upfront output limitation. There is no filler or repetition.
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 four parameters, no annotations, and no output schema, the description is insufficient. It does not explain how to specify the robots.txt URL or host, what 'group counts' contain, or what the response looks like, leaving too much for the agent to guess.
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?
Although schema coverage is 100%, the parameter descriptions are misaligned with the tool's purpose: url is described for normalizing/citing, json for validation, zone for timezone, and none mention robots.txt. The description also does not clarify whether url or host is the intended target, making parameter selection ambiguous.
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 clearly identifies a specific verb and resource: 'Fetch a public robots.txt' and specifies the output as 'group counts only.' It is unambiguous about the core function, though it does not explicitly differentiate from sibling tools; no sibling obviously covers robots.txt.
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 alternatives, no prerequisites, and no indication of which parameter supplies the robots.txt location. The agent must infer usage from the tool name and description alone.
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: citation and normalize-url both return URL origin/host information, while timezone and utc-time both provide current time. The descriptions help separate most tools, but compatibility is vague and could be confused with classification or request-checking tools.
Names use lowercase hyphenation and are generally readable, but they mix verb-led forms like inspect-robots, normalize-url, and validate-json with noun-led forms like domain-shape, status-catalog, and utc-time. There is no consistent verb_noun or noun_verb convention across the set.
11 tools is a reasonable count, but for a server named 'Nano ID shape check' the scope feels diffuse, with URL, time, JSON, and HTTP status utilities included. Several tools do not clearly earn their place under that stated purpose.
The server claims a narrow Nano ID focus, yet only one tool directly supports it, while URL, JSON, time, and robots checks are shallow one-offs. There are no tools for generating or custom-validating Nano IDs, and URL handling stops at normalization without redirects or deeper request inspection.