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?
With no annotations, the description must fully disclose behavioral traits. It does mention that the body is discarded, which is a useful privacy detail, but this is already documented in the json parameter's schema description. The description does not state the return format (e.g., boolean, validation error) or how 'valid' is determined, leaving critical behavioral information omitted.
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 sentence, which is concise, but it is under-specified. It fails to clarify which parameter is the 'body' and what the outcome of the validation looks like. It is not optimally front-loaded with concrete, actionable information.
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?
There is no output schema and no annotations, leaving a substantial gap. A JSON validation tool should explain what the tool returns (e.g., a boolean, success/error status) or any side effects beyond discarding the body. The description is too thin for an agent to invoke the tool confidently.
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 description coverage is 100%, so the schema already documents all four parameters. The tool description adds no parameter-specific meaning; it only references a generic 'body' that presumably maps to the json parameter. Baseline 3 applies since the schema carries the burden.
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 clear action ('Check whether a body is valid JSON') with a specific verb and resource. However, it does not distinguish this tool from sibling tools like normalize-url or cite, and the word 'body' is vague without referencing the json parameter.
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. It does not mention typical use cases, exclusions, or any context that would help an agent decide between this and 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.
Most tools have distinct outputs, but there is real overlap: http-404 is a subset of status-catalog, timezone overlaps utc-time, and citation/normalize-url/domain-shape all parse URLs in slightly different ways. The descriptions clarify intended uses, so an agent can usually pick correctly, but the boundaries are not crisp.
Names are all lowercase kebab-case, which provides a surface-level consistency, but the structural pattern is mixed: single nouns, noun-noun compounds, and imperative verb-noun forms. This makes the naming scheme less predictable than a uniform verb_noun or noun-based convention.
Eleven tools is within a reasonable numeric range, but the set is not tightly scoped: URL/HTTP tools are mixed with timezone, JSON, and compatibility tools. A more focused HTTP utility server could easily justify fewer or more cohesive tools.
The inferred domain is URL/HTTP inspection, and the set covers normalization, status codes, and robots, but it lacks obvious related operations such as HTTP headers, redirects, or URL decoding. The presence of unrelated time and JSON tools makes the surface feel arbitrary rather than deliberately complete.