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 present, the description carries the full burden of disclosing behavior. It only mentions fetching and returning counts, but does not explain error handling, rate limits, or any side effects. This is insufficient for a network-fetching 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?
The description is a single concise sentence, but it omits essential information about how parameters contribute to the task. It is too sparse to be fully useful, yet it is not overly verbose.
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 description is inconsistent with its parameters, making it incomplete. There is no explanation of how 'url', 'host', 'json', or 'zone' relate to fetching robots.txt, and no output schema is provided. This creates significant ambiguity for an agent.
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 parameter descriptions are clearly copy-pasted from other tools, such as 'JSON text to validate' and 'IANA timezone name', and bear no relation to fetching robots.txt. The schema covers all parameters, but the descriptions are misleading and do not explain how they affect the group counts.
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 'Fetch' and resource 'robots.txt', and specifies the output as 'group counts only', which gives a clear purpose. However, it does not differentiate from sibling tools, but the core action is understandable.
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 description provides no guidance on when to use this tool versus alternatives like 'normalize-url' or 'validate-json'. It lacks any contextual cues or scenarios that would help an agent decide to invoke this 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.
Tools are individually distinct in their operations, but the mix of URL, timezone, JSON, and temperature topics creates confusion about which tool applies to a given task. Names like 'compatibility' and 'citation' are vague and could be misinterpreted.
Naming conventions are inconsistent: some tools use hyphenated lower-case (f-to-c, iana-zones), others use single words (citation, timezone), and some use multi-word phrases (normalize-url, validate-json). This lack of a uniform pattern reduces predictability.
At 11 tools, the count is within the typical range, but it feels excessive for a server ostensibly dedicated to Fahrenheit-to-Celsius conversion. The number is inflated by unrelated utilities, making the set poorly scoped for the stated purpose.
For a Fahrenheit-to-Celsius converter, there is only one relevant tool (f-to-c). Essential operations like Celsius-to-Fahrenheit, Kelvin conversions, or batch conversions are missing, so the domain coverage is severely incomplete.