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 mentions that the body is discarded after the check, offering some transparency about non-persistence. However, it does not disclose what happens on invalid JSON, whether an error is thrown or a boolean returned, or if there are any side effects beyond validation. No annotations exist to supplement this.
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 succinct and to the point, using a single sentence to convey the core action. It avoids unnecessary verbosity. The structure is fine, though the ambiguity of 'body' slightly detracts from otherwise clean wording.
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 definition is incomplete because it fails to explain how the url, host, and zone parameters relate to validating JSON. Without clarity on these inputs, an agent cannot correctly formulate a call. The presence of irrelevant parameter descriptions undermines the overall completeness, leaving critical gaps in understanding.
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?
Only the 'json' parameter has a relevant description ('JSON text to validate; discarded after the check'). The other three parameters—url, host, zone—have descriptions that are clearly mismatched (e.g., 'HTTPS URL to normalize or cite', 'Public hostname', 'IANA timezone name') and unrelated to JSON validation, making them actively misleading for an agent.
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 function: checking whether a body is valid JSON. This distinguishes it from sibling tools like citation or normalize-url, which serve different purposes. However, the term 'body' is ambiguous—it could refer to the 'json' parameter or an external HTTP body, so it's not perfectly crisp.
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 explicit guidance on when to use this tool versus alternatives, nor does it explain how to supply the JSON to validate. While there is no direct sibling for JSON validation, the lack of usage context or parameter instructions leaves the agent uncertain about invocation.
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 have distinct purposes, but citation and normalize-url both inspect URLs with overlapping fields, and timezone/utc-time/iana-zones are related. Descriptions clarify the differences, so ambiguity is minimal.
All tool names use lowercase with hyphens, following a consistent pattern (e.g., normalize-url, validate-json, utc-time). No mixed conventions or irregular verbs.
With 11 tools, the count is well within the typical 3-15 range. Each tool appears to serve a distinct utility, and the number is reasonable for a general-purpose toolkit.
The tools form a disjointed collection of unrelated utilities (URLs, time, HTTP, JSON, robots, language tag) with no coherent domain. There is no obvious lifecycle or CRUD pattern, and the set lacks depth in any single area, making it incomplete for any defined purpose.