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 a useful behavioral trait: 'The body is discarded' implies the operation is non-persistent and side-effect-free. However, with no annotations and no output schema, it does not explain return values, error handling, or what happens with invalid JSON, leaving a notable transparency gap.
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?
Two short sentences are front-loaded and contain no filler. The purpose and a key behavioral note are stated directly, making the description easy to parse quickly.
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?
For a tool with four parameters, no output schema, and no annotations, the description is too sparse. It does not specify which parameter holds the JSON body, what a successful or failed validation returns, or how to interpret the extraneous parameters. More detail is needed for an agent 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?
Schema descriptions cover all four parameters, so the baseline is 3. The description itself adds no parameter-level meaning, leaving the agent to infer that the 'json' parameter is the relevant one. It does not clarify why 'url', 'host', and 'zone' are present or how they relate to the validation.
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 verb and resource: 'Check whether a body is valid JSON.' This conveys the core purpose without ambiguity. However, it does not explicitly differentiate itself from sibling tools like 'json' or 'normalize-url'.
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 given on when to use this tool versus alternatives. It does not mention conditions, exclusions, or which sibling tool to prefer in different scenarios. The sentence 'Check whether a body is valid JSON' implies context but never states it explicitly.
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.
json-ok and validate-json are effectively duplicate JSON validity checks, and several URL/HTTP tools (citation, normalize-url, domain-shape) have overlapping hostname/status concerns. compatibility is too vague to distinguish reliably from the other HTTP-related tools.
The names are all lowercase hyphenated, but they mix noun phrases (citation, timezone), imperative verbs (normalize-url, validate-json), and adjective constructions (json-ok). There is no consistent verb_noun or resource_action pattern, and the same JSON operation is called two different names.
Eleven tools is not inherently too large, but the set is not tightly scoped to the apparent 'JSON validity' purpose and bundles URL, robots, HTTP, and time utilities. The duplicate JSON validation tools also make the count feel padded rather than earning their places.
There are useful clusters for URL inspection, HTTP status, time, and JSON validity, but no clear workflow connects them and compatibility remains unexplained. Within a broad safe-web/utility interpretation the basics are present, yet obvious helpers such as header inspection or a single unified JSON validator are missing.