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JSON-Schema (2020-12) validate + explain (paid $0.001)

jsonschema

PAID $0.001. Validate a value against a JSON Schema (draft 2020-12) and explain every error in plain English (which property, what was wrong, allowed values). Args: schema (object), data (any). Without payment returns the x402 challenge; pass x_payment to settle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe value to validate against the schema.
schemaYesA JSON Schema (draft 2020-12) object.
x_paymentNox402 payment payload (base64) for this PAID tool. If supplied it is forwarded as the X-PAYMENT header to settle the $0.001 call and return the real result instead of a 402 challenge. Omit to get the price challenge first.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure, and it does so well: it discloses the $0.001 cost, the x402 challenge behavior when payment is missing, and the promise of plain-English error explanations. It also mentions the args at a high level. It does not state whether the operation has side effects (it is inherently read-only), but this is implicit for validation.

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 two sentences long, front-loaded with the critical payment warning, and then immediately states the core functionality. Every word serves a purpose: the cost, the validation behavior, the error explanation, the arguments, and the payment workflow are all covered. No fluff or redundancy.

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

Completeness4/5

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

For a paid tool with no output schema, the description provides sufficient context for an agent to select and invoke it: the validation target, the error explanation behavior, the cost, and the payment challenge/settle workflow. It does not describe the success-return format, but that is less critical given the lack of an output schema and the tool's clear functional scope.

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?

The input schema already provides full descriptions for all three parameters, so the baseline is 3. The description adds a small amount of operational meaning by explaining x_payment's role in settling the payment and noting data can be any value. However, it does not add significant depth beyond what the schema already declares, so a 3 is appropriate.

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

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: validating a value against a JSON Schema (2020-12) and explaining errors in plain English. This distinguishes it from the sibling tools (convert, encode, hash, etc.), which handle different operations. The verb 'validate' and the specific resource 'JSON Schema' make the purpose unambiguous.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool: whenever JSON Schema validation with human-readable error explanations is needed. It also gives explicit usage guidance for the payment flow: omit x_payment to receive the x402 challenge, or include it to settle the call. It does not explicitly name alternatives, but no sibling offers validation, so the intended use is clear.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct operation: unit conversion, cron parsing, currency conversion, date math, diff, encoding, hashing, ID generation, JSON schema validation, regex, RRULE expansion, text transforms, and timezone conversion. Even related tools like convert, currency, and timezone are clearly separated by domain, with descriptions that eliminate ambiguity.

Naming Consistency5/5

All tool names are lowercase single-word identifiers without separators or camelCase, forming a clean and predictable pattern. While some are verbs (convert, diff, encode) and others nouns (cron, currency, id), the uniform naming style ensures consistency.

Tool Count5/5

13 tools is well-scoped for a general-purpose utility belt. Each tool covers a common utility without redundancy, fitting comfortably within the ideal 3-15 range.

Completeness5/5

The tool surface covers a broad range of utilities: unit and currency conversion, date/time handling (datemath, timezone, cron, rrule), text processing (text, encode, regex, diff), cryptography (hash), ID generation, and schema validation. No obvious gaps exist for the stated purpose.