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JSON Schema strict-mode validator ($0.01)

json_schema_lint
Idempotent

[Paid x402 / X-Bazaar-Key: 0.01 USDC] Validate a JSON Schema object definition (type, properties, required subset, additionalProperties=false) for LLM structured output compatibility.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "json_schema_lint"
  }
}

Input Schema

NameRequiredDescriptionDefault
propertiesNoComma-separated property names

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3/5.0
Behavior3/5

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

The description adds genuinely useful context beyond the annotations by disclosing the x402 payment mechanism and price (0.01 USDC via X-Bazaar-Key), which explains the non-read-only hint. However, it says nothing about what rules are enforced beyond the parenthetical hints, whether failures return errors or a report, or how payment failure is surfaced.

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?

One sentence with the payment tag front-loaded, so cost is visible before the task. It is efficient, though the parenthetical constraint list makes it a bit dense for its length.

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?

No output schema exists, so the description should say what a validation result looks like (pass/fail, error list) and it does not. For a paid tool whose input contract is unclear, this leaves the agent short of what it needs to call and interpret results confidently.

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 coverage is reported as 100%, but the schema itself is ambiguous: it documents only a single optional 'properties' string and allows additionalProperties, so how the actual schema-to-validate is supplied is unclear. The description does not clarify the input shape or the comma-separated convention, so it fails to compensate for that ambiguity.

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?

States a specific verb (Validate) and resource (a JSON Schema object definition) plus the goal (LLM structured output compatibility). It is clear what the tool does, but it never distinguishes itself from adjacent linters in the sibling set (openapi_tool_lint, mcp_manifest_lint, llms_txt_lint), so the agent must infer which linter applies.

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?

The mention of 'LLM structured output compatibility' implies a use case, but there is no explicit when-to-use, when-not-to-use, or prerequisite guidance. With a large family of sibling lint tools, the absence of routing guidance is a real gap.

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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