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?
There are no annotations, so the description alone must disclose behavior. It mentions 'public' and 'counts only', but says nothing about network behavior, failures when robots.txt is absent, or why parameters like 'json' and 'zone' are accepted. An agent would be surprised by the schema mismatch.
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?
Single sentence with no wasted words and the core function front-loaded. However, the brevity creates opacity, omitting any explanation of the mismatched parameters, so the structure earns only a mid score.
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 optional-looking parameters, no annotations, and no output schema, yet the description explains neither the role of those parameters nor what 'group counts' look like. This is not enough context for an agent to call the tool correctly.
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 descriptions cover 100% of parameters, but they are generic and unrelated to robots.txt ('HTTPS URL to normalize or cite', 'JSON text to validate; discarded after the check', 'IANA timezone name'). The tool description adds no mapping from url/host/json/zone to the fetch-and-count operation, so an agent cannot determine how the parameters relate to the stated 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?
States a concrete action ('Fetch a public robots.txt') and a constrained return value ('group counts only'), which distinguishes it from a full-content fetcher. It does not define what a 'group' is or name an alternative, but the core purpose is immediately legible.
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?
Offers no statement of when to prefer this tool, what it should not be used for, or how it compares to sibling tools such as citation or validate. The 'only' qualifier implies a minimal check, but selection is left entirely 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.
The time-related tools (epoch-ms, utc-time, timezone, iana-zones) are distinguishable, but several URL tools overlap in input and output: citation and normalize-url both expose host/URL components, and compatibility is vague about what it classifies. An agent could misselect between the URL inspection tools despite helpful descriptions.
Names are mostly lowercase with hyphens, but there is no consistent grammatical pattern: noun phrases like epoch-ms, utc-time, and status-catalog mix with imperative verbs like inspect-robots, normalize-url, and validate-json. This inconsistency makes the naming style readable but unpredictable.
Eleven tools is a reasonable count on its own, but the set is not tightly scoped to the server's apparent identity of Unix epoch milliseconds; it mixes time, URL, robots, status code, and JSON utilities. This feels like a general utility grab-bag rather than a focused toolset.
For the time domain implied by the server name, there are no epoch-to-date conversions, formatting helpers, or timezone offset details, leaving obvious gaps. The URL/request utilities are similarly fragmentary, covering shape and status but not full content retrieval or more useful metadata, so the surface feels incomplete for any single stated purpose.