Return host, scheme, and HTTP status for a URL. Page content is not stored.
| 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. 'Page content is not stored' is a genuine behavioral disclosure, but it is the only one. The description omits whether the URL is fetched, what side effects occur, auth requirements, rate limits, or failure behavior — significant gaps for an unannotated tool.
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?
Two short sentences with zero waste. The primary operation is front-loaded, followed by a single privacy-relevant qualifier. Every word earns its place.
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 4 parameters, none required, no output schema, and no annotations. The description explains only the URL-related behavior and never addresses the json and zone parameters, output format, possible return values, or error conditions. An agent would not know how to call this tool correctly for non-URL inputs.
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. The description adds nothing beyond the schema's parameter documentation. Notably, the description only mentions URL while the schema includes unrelated-looking parameters (json, zone); the description does not bridge how those fit the tool's purpose.
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 ('Return') and resource ('host, scheme, and HTTP status for a URL'), making the core function clear. It does not explicitly differentiate from sibling tools, which matters given the confusing sibling list, but the primary 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?
No guidance is given on when to use this tool versus alternatives, no usage context, and no exclusions. The single sentence does not address selection criteria or mention any sibling tool.
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.