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validate-json

Check whether a body is valid JSON. The body is discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears full responsibility. It usefully discloses that the body is discarded, establishing a non-persistence side effect. Yet it does not disclose what the tool returns on valid or invalid JSON, nor does it reconcile the many unrelated schema properties with the stated JSON-only purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no redundant wording. The core purpose is front-loaded, and every word contributes to the definition. It is a model of concise, scannable tool documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Overall, the definition is minimally viable but leaves open several questions: which parameter represents the body, what happens when the JSON is invalid, and why the schema includes many unrelated parameters. With no output schema, the return value is also unspecified, so an agent may need to infer behavior from the tool's name alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides detailed descriptions for every parameter, including a clear one for 'json' ('JSON text to validate; discarded after the check'). The description itself does not explicitly map the term 'body' to the 'json' parameter, but the schema already conveys enough meaning for an agent to infer the correct parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Check') and target ('whether a body is valid JSON'), clearly indicating the tool validates JSON syntax. It is distinguishable from sibling shape-checkers by its focus on JSON, though it does not explicitly name an alternative or contrast with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended usage is implied: use this when you need to determine if a body is valid JSON. However, there is no explicit guidance about when not to use it, what alternatives exist, or any prerequisites or context that would route an agent to this tool rather than a different one.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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