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Port 22

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. Changed5 schema fields changed
    • addedInput schema / properties / city
      Added value: +{
      +  "description": "City name for a public weather hint; discarded after the call",
      +  "type": "string"
      +}
    • addedInput schema / properties / feed
      Added value: +{
      +  "description": "Public RSS or Atom URL; titles discarded",
      +  "type": "string"
      +}
    • addedInput schema / properties / path
      Added value: +{
      +  "description": "File path to check; no disk access",
      +  "type": "string"
      +}
    • addedInput schema / properties / query
      Added value: +{
      +  "description": "Search text; discarded after the length check",
      +  "type": "string"
      +}
    • addedInput schema / properties / ref
      Added value: +{
      +  "description": "Git ref name; discarded after the shape check",
      +  "type": "string"
      +}
  2. First observed

TDQS

B3.2/5.0
Behavior2/5

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

Annotations are none, so the description carries the full burden. It discloses the key behavior that the body is discarded, which is a notable side-effect (no persistence). However, it does not disclose other behaviors such as whether the JSON is parsed, what 'valid' means exactly (e.g., strict vs. lenient), error handling, or rate limits. For a tool with no annotations, this is a minimal but useful disclosure, yet incomplete.

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 extremely concise: two sentences communicate the core function and the side-effect of discarding the body. Every word earns its place. It is front-loaded with the main purpose and the discarding note is a critical behavioral caveat. There is zero waste.

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?

The tool has 4 parameters, none required, no output schema, and no annotations. The description is simple and covers the main purpose, but it leaves gaps: what does 'valid' mean, what happens on invalid JSON (error? silent false?), and what the output format is (boolean, error message, etc.). Without an output schema or annotations, the agent is left uncertain about the return behavior, which is essential for correct invocation.

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?

Schema description coverage is 100%, so all four parameters already have descriptions: url, host, json, zone. The description adds no new parameter semantics beyond the schema, but the schema itself is clear. The parameter descriptions seem generic and may not fully align with the tool's purpose (why would a JSON validator need url, host, zone?), which could confuse, but the baseline 3 applies because schema coverage is high.

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 clearly states the tool's purpose: 'Check whether a body is valid JSON' and that 'the body is discarded'. It identifies the specific verb (check) and resource (JSON body), which is understandable. However, it doesn't explicitly differentiate from siblings, though the sibling names (normalize-url, cite, etc.) suggest different domains, so the clarity is sufficient without explicit differentiation.

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 description implies the tool is used for validating JSON and discarding it, but does not provide explicit guidance on when to use this tool versus alternatives. It mentions no exclusions or conditions. The context of sibling tools suggests validation is a distinct action, but the description itself offers no when-to-use or alternative comparisons, leaving it to the agent to infer.

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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