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 present, so the description carries full burden. It discloses the core behavior: a read-only network fetch of a public robots.txt returning only group counts. It does not mention error handling, redirects, or rate limits, but it covers the main behavioral expectation.
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?
Exactly one sentence, front-loaded with the key action, precise about the returned data. Every word contributes; 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?
With 4 parameters, 0 required, no output schema, and no annotations, a single sentence is insufficient. The definition fails to explain how the unrelated-looking parameters relate to the robots.txt fetch, what the response structure is beyond group counts, or how to invoke it 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?
The input schema has 100% description coverage, but the parameter descriptions (normalize/cite, hostname, validate JSON, timezone) do not align with the stated robots.txt purpose. The description adds no guidance on which parameter should be used as the fetch target, so an agent cannot reliably map the schema to 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?
States a specific verb and resource ('Fetch a public robots.txt') and scopes the return value ('group counts only'), making the core purpose clear. It does not differentiate from siblings, but is easily distinguishable by name and intent. The apparent mismatch with the input schema adds ambiguity but does not erase the stated purpose.
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?
Provides no when-to-use guidance, no when-not-to-use conditions, and names no alternatives. The phrase 'group counts only' implies a lightweight use case, but that is left to inference rather than stated.
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 are distinct, but citation and normalize-url both accept URLs and return host/scheme, so an agent could select the wrong one. timezone/utc-time/iana-zones and compatibility/status-catalog also have overlapping territory, though the descriptions provide some separation.
Names are readable but follow no single convention: some are verb_noun (normalize-url, validate-json, inspect-robots), while others are noun compounds or standalone nouns (timezone, status-catalog, compatibility). This mix is not chaotic, but it lacks a predictable pattern.
11 tools is not excessive, and each utility is small and self-contained. However, the set feels like a grab bag of unrelated utilities rather than a tightly scoped server, and some tools could plausibly be consolidated.
The tools cover basic URL inspection, HTTP status, time lookups, JSON validation, and random generation, but the server's intended domain is unclear. Within that mix, there are notable gaps such as no timezone conversion, no URL encoding/decoding, and no way to inspect HTTP headers, so coverage feels incomplete.