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KSUID character length

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

C2.3/5.0
Behavior2/5

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

There are no annotations, so the description must carry the behavioral burden. It only says 'The body is discarded,' which hints at no side effects, but it doesn't disclose what happens with invalid JSON, the return format, or how the other parameters are treated. The mismatch between 'body' and the schema's 'json' parameter adds confusion.

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

Conciseness3/5

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

The description is appropriately short (two sentences) and front-loads the purpose, which is good. However, it is too sparse to be useful—it omits crucial context about parameters and behavior. It is concise but not effective.

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

Completeness1/5

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

Given the tool's complexity (9 parameters, no output schema, no annotations), the description is severely incomplete. It doesn't explain the role of each parameter, the expected input format, the return value, or when to use it. An agent cannot reliably determine how to construct a valid call.

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

Parameters2/5

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

The description adds no meaningful parameter information beyond the schema. The schema already describes each parameter with vague phrases like 'discarded after the shape check,' but the description doesn't explain how these relate to JSON validation or what 'shape check' means. Since schema coverage is 100%, the baseline is 3, but the description fails to compensate for the schema's ambiguity and even introduces a new term ('body') not present in the schema.

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

Purpose3/5

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.' This is clear, but it doesn't distinguish from sibling validators and introduces ambiguity by saying 'body' while the schema has a 'json' parameter. The presence of nine unrelated parameters (ref, url, city, feed, host, path, zone, query) in the schema contradicts the narrow JSON-only purpose, reducing clarity.

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?

No guidance is provided on when to use this tool vs alternatives. It doesn't mention any conditions, exclusions, or sibling tools. An agent has no way to know if this is the right tool for a given validation task beyond the name.

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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