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Teaspoons to milliliters

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

C2/5.0
Behavior2/5

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

No annotations are provided, so the description carries full behavioral disclosure burden. It only states 'The body is discarded,' which is a limited side-effect note. It does not mention that the tool is read-only, whether network/disk access is involved (though schema notes 'no disk access' for path), or any other operational characteristics. This is insufficient for a tool with no annotation safety net.

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

Conciseness2/5

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

The description is extremely short (two sentences) and front-loads the purpose, which is good. However, it omits essential context for a tool with 9 parameters, making it under-specified rather than concise. A few more sentences explaining parameter usage and differentiation would justify a higher score.

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 has 9 optional parameters, no annotations, and no output schema, the description is severely incomplete. It does not explain why the other seven parameters are present, how they interact with the JSON validation, or what the expected input format is. The description alone is wholly inadequate for an agent to correctly invoke this tool.

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?

Schema description coverage is 100%, so the baseline is 3. However, the description adds no value beyond the schema and actually introduces an undefined term 'body' that does not match any parameter. It fails to clarify which parameter holds the JSON (json vs path) or why the other seven parameters exist. The schema already documents each parameter, but the description should at least map the primary input, which it does not.

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 clear verb+resource: 'Check whether a body is valid JSON.' However, it uses 'body' without mapping to any schema parameter (likely 'json' or 'path'), which is ambiguous. It also doesn't differentiate from sibling shape-check tools like domain-shape or github-repo-shape, leaving the agent to infer the scope.

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

Usage Guidelines1/5

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

No guidance is given on when to use this tool versus alternatives. With 28 sibling tools, many of which validate shapes of specific inputs, the description provides no exclusions or conditions for selection. The agent is left to guess when validate-json is appropriate.

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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