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?
No annotations are provided, so the description carries the behavioral disclosure burden. It explicitly states that the body is discarded, which is useful, but it does not describe return values, error behavior, or whether the other schema properties are used. This is helpful but incomplete.
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 two short sentences with no wasted words. The purpose is front-loaded, and the disposal behavior is an important, concise addition.
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?
With four parameters, no required fields, no output schema, and no annotations, the description is underspecified. It does not state what the tool returns for valid or invalid JSON, which parameters are actually required for the check, or how to interpret errors. An agent would likely need to probe the tool to use it 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 baseline is 3. The description adds no parameter-level meaning on top of the schema, and the schema does document each property. However, url, host, and zone appear unrelated to JSON validation, and the description does nothing to disambiguate their role.
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 and resource: 'Check whether a body is valid JSON,' and adds the non-obvious detail that the body is discarded. It is more informative than a tautology, though it does not name sibling tools or explain why the schema also includes url, host, and zone.
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?
There is no guidance about when to use validate-json versus sibling tools, no exclusions, and no mention of prerequisites or typical use cases. The only implicit hint is the tool name itself.
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 cluster into URL/HTTP and time-related groups, but within each cluster the purposes are mostly distinguishable. citation, normalize-url, and domain-shape all touch hostnames, while timezone, utc-time, and weekday-utc all return current time data, so an agent could briefly hesitate when selecting among them.
All names use lowercase hyphens, but there is no consistent verb_noun or noun pattern. Some tools use verb-object naming like inspect-robots and normalize-url, while others are plain nouns like citation, timezone, and status-catalog, making the set feel inconsistent.
Eleven tools is a reasonable count for a utility server and does not feel bloated. However, the selection spans many unrelated concerns—URL parsing, time, JSON validation, robots.txt, HTTP status—so the set feels broader than a single focused purpose.
For a privacy-focused URL/HTTP utility set, there are notable gaps such as no redirect or header inspection, and for time utilities there is no timezone conversion tool. The surface covers basic atomic operations but lacks the cohesive lifecycle or workflow coverage that would make it feel complete.