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 full burden. It says 'return group counts only', which partially clarifies output, but it does not disclose network behavior, error conditions, rate limits, or whether the fetched content is cached. For a fetch operation, that leaves notable behavioral gaps; an agent might reasonably expect more detail about what 'inspect' implies (e.g., does it block on network? can it fail?).
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 that conveys the core operation and output scope efficiently. There is no wasted wording, though it could have added a brief parenthetical about which parameter to use without becoming bloated.
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 no annotations, no output schema, and four optional-looking parameters, the description leaves an agent guessing about the actual calling pattern. The tool fetches a robots.txt but also offers parameters like json, zone, and url that are described as unrelated actions ('normalize or cite', 'validate', 'IANA timezone name'). That mismatch is confusing and makes the description incomplete for reliable invocation.
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 each parameter has some textual description in the schema. However, the tool description says 'return group counts only', which does not explain how any of the four parameters relate to the operation. The schema descriptions themselves are minimal (e.g., 'HTTPS URL to normalize or cite', 'Public hostname'), and the description does not compensate by clarifying which parameter is actually required or how they interact. Baseline 3 applies because coverage is high, but no added semantics are given beyond the schema.
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?
States a specific verb ('Fetch') and resource ('public robots.txt') and scopes the behavior to 'group counts only'. The name 'inspect-robots' matches the description well. It does not explicitly distinguish from siblings (citation, which suggests related tools), but the resource and output scope are clear on their own.
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?
No guidance is given about when to use this tool versus alternatives. The sibling list includes citation, but the description does not say when to prefer this over citation or any other tool. An agent must infer usage context from the 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 have overlapping concerns: citation, normalize-url, and domain-shape all analyze URLs/hostnames, while timezone, utc-time, and iana-zones all relate to time. The purpose of compatibility is vague and could be confused with the URL inspection tools. Only a few tools like slug-ok and validate-json are clearly distinct.
All names use lowercase hyphenation, which is consistent, but the pattern is mixed: some are verb phrases (normalize-url, inspect-robots, validate-json), while others are bare nouns (citation, compatibility, timezone). There is no unified verb_noun convention, though the names remain readable.
Eleven tools is not an unreasonable count by itself, but the tool set is unfocused for a server named 'Slug character check.' Most tools address unrelated concerns such as time, URLs, HTTP status, and JSON, making the collection feel padded rather than purpose-built.
The server lacks a coherent domain: slug checking has only one thin tool, URL utilities have no encoding/decoding or query-param handling, and time utilities lack conversions or formatting options. For any single stated purpose, the surface has significant gaps and no end-to-end workflow.