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', which gives a partial behavioral hint, but it does not disclose what the tool returns (e.g., a boolean, an error message), whether it has side effects beyond discarding the body, or if it is read-only. With no annotations, this lack of detail leaves significant ambiguity.
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 extremely concise, consisting of two short sentences that directly state the core function and a key behavioral note. There is no redundancy or unnecessary detail, making it easy to parse and understand 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?
The description lacks essential context: it does not explain what constitutes a 'body', how the tool integrates with the other parameters (url, host, zone), or what the expected output format is. Given the sibling tools, the description does not sufficiently situate this tool within a broader workflow, leaving the agent with incomplete information for correct invocation.
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?
While the schema provides descriptions for all parameters, many are irrelevant to the tool's purpose (e.g., url, host, zone). The only relevant parameter 'json' is described as 'JSON text to validate', but the tool description does not elaborate on how it relates to the other parameters or the 'body' concept. The description adds minimal clarity beyond the schema.
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 verb 'Check' and the object 'whether a body is valid JSON', which precisely defines the tool's purpose. It is unambiguous and easily distinguishable from the sibling tools that handle URLs, timezones, or other data transformations.
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 guidance on when to use this tool versus alternatives, nor any prerequisites or conditions. It simply states the action without any usage context, leaving the agent to infer appropriate invocation scenarios.
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, such as byte-count, validate-json, and utc-time. However, citation and normalize-url both handle URLs, and timezone and utc-time both provide time information, which could lead to occasional misselection.
Names are mostly lowercase with hyphens, but the pattern is inconsistent: some are nouns (byte-count, timezone, status-catalog) while others are verbs (inspect-robots, normalize-url, validate-json). There is no clear verb_noun or noun_verb convention across the set.
11 tools is a reasonable count for a utility server covering URLs, time, robots, and data validation. Each tool does something different, though a few are quite trivial, making the set slightly broad but not excessive.
The tools cover several common utility categories like URL normalization, current time, timezone lookup, and JSON validation. However, the scope is broad and shallow, leaving obvious gaps such as domain lookups, HTTP request mechanics, or date formatting, and there is no unifying workflow to judge full coverage.