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 full burden. It discloses that the operation is a read of a public resource and that the output is limited to group counts rather than full content, which is useful. It does not cover failure behavior (e.g., missing robots.txt), what 'public' requires, or how the non-URL parameters factor into behavior, so transparency is adequate but thin.
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; every word earns its place. It is slightly under-specified, but that is a completeness concern, not a conciseness one.
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?
There is no output schema or annotations, and the description never explains what 'group counts' means, what the response looks like, or how the optional host/json/zone parameters relate to the fetch. For a tool with four optional parameters and zero structured context, this leaves 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?
Schema coverage is 100%, which normally earns a baseline of 3, but the parameter descriptions conflict with the tool's stated purpose: url is described as 'HTTPS URL to normalize or cite' rather than the source of a robots.txt, and json/zone appear unrelated to robots.txt inspection. The description adds no parameter guidance, so an agent cannot confidently determine which parameters are relevant.
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 concrete resource (a public robots.txt), and a precise return scope ('group counts only'), which clearly differentiates it from the sibling fetch-robots that would return the full file. It does not name the sibling explicitly, and the parameter schema hints at other unrelated behaviors, but the core purpose is unambiguous.
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 phrase 'return group counts only' implies the tool is for when an agent needs only the group counts rather than the full robots.txt content, so the intended usage is inferable. There is no explicit when-to-use instruction, exclusion, or named alternative, leaving the choice between inspect-robots and fetch-robots to inference.
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 distinct outputs, but there is real overlap: http-404 is a subset of status-catalog, timezone overlaps utc-time, and citation/normalize-url/domain-shape all parse URLs in slightly different ways. The descriptions clarify intended uses, so an agent can usually pick correctly, but the boundaries are not crisp.
Names are all lowercase kebab-case, which provides a surface-level consistency, but the structural pattern is mixed: single nouns, noun-noun compounds, and imperative verb-noun forms. This makes the naming scheme less predictable than a uniform verb_noun or noun-based convention.
Eleven tools is within a reasonable numeric range, but the set is not tightly scoped: URL/HTTP tools are mixed with timezone, JSON, and compatibility tools. A more focused HTTP utility server could easily justify fewer or more cohesive tools.
The inferred domain is URL/HTTP inspection, and the set covers normalization, status codes, and robots, but it lacks obvious related operations such as HTTP headers, redirects, or URL decoding. The presence of unrelated time and JSON tools makes the surface feel arbitrary rather than deliberately complete.