Check whether a body is valid JSON. The body is discarded.
| 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?
The description discloses one behavioral aspect: 'The body is discarded.' However, it does not clarify whether the tool performs a read-only check, what it returns, or any side effects beyond discarding the input. The lack of annotations leaves most behavioral details undocumented.
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 very concise, using only two sentences. It is reasonably well-structured, but the extreme brevity and contradictory parameters reduce the effectiveness. Still, it does not waste words.
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 is highly incomplete for an agent. There is no output schema, no usage context, and the parameter semantics do not align with the described purpose. The agent would have no way to know what to provide or what to expect as a result, especially given the unrelated parameters.
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 schema descriptions for parameters are misleading relative to the tool's stated purpose. While the 'json' parameter is described as 'JSON text to validate', other parameters like 'url', 'host', and 'zone' are described for unrelated purposes (normalize, cite, timezone). The description adds no clarification and the parameter set appears inconsistent with the tool's function.
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 clearly states the action: 'Check whether a body is valid JSON.' It also explains the outcome that the body is discarded. However, the stated purpose conflicts with the parameter set (url, host, zone), which introduces ambiguity about the actual functionality.
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 provided on when to use this tool versus alternatives. There is no mention of conditions or scenarios that would make this tool preferable, nor any criteria to distinguish it from sibling tools.
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.