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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

C2.9/5.0
Behavior2/5

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

The sentence 'The body is discarded' is the only behavioral disclosure, hinting at statelessness and no persistence. But the description does not explain return behavior, error handling for invalid JSON, or any encoding constraints. With no annotations present, the description carries the full burden of behavioral transparency and fails to cover these key aspects.

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

Conciseness4/5

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

The description is extremely concise and front-loads the main action in the first sentence. Both sentences carry some information, but the brevity sacrifices important context such as return format and parameter relevance. It is well-structured and efficient, but leans toward under-specification for a multi-parameter tool.

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

Completeness2/5

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

For a tool with seven parameters, no output schema, and no annotations, this description is far too thin. It does not define the result of validation (e.g., boolean vs throw), explain how parameters relate to the 'body', or provide enough detail for an agent to invoke it correctly. The schema descriptions help, but the description itself leaves significant gaps.

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?

All seven parameters in the input schema have descriptive text, so schema coverage is effectively complete (high coverage baseline of 3). The tool description adds no operational detail about the parameters and even introduces ambiguity with its reference to 'body' rather than the actual 'json' parameter. Since the schema already does the heavy lifting, a baseline score of 3 is appropriate.

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 the core action clearly: 'Check whether a body is valid JSON.' The tool name reinforces the resource, and the action is specific enough to distinguish it from pure fetch or URL-checking siblings. However, the description's use of 'body' is ambiguous because the input schema exposes a 'json' parameter rather than a named 'body' parameter, and no sibling differentiation is provided.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as fetch-status or wiki-title-ok, nor any exclusions or conditions. The description simply states the operation, leaving the agent to infer the appropriate context and dependencies.

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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