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lazymac2x

lazymac-mcp

json_schema_validator

Validate JSON data against schemas, auto-infer schemas from data, generate TypeScript types, and create mock data for testing.

Instructions

Auto-infer schemas, validate, generate TypeScript, mock data, diffs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoFree-form params object — passed as query string for GET, JSON body for POST
Behavior2/5

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

With no annotations provided, the description carries full burden but only lists capabilities without behavioral context. It doesn't disclose whether operations are read-only or mutative, what permissions might be needed, rate limits, or what happens during validation failures—critical gaps for a tool with multiple functions.

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?

The description is extremely concise—a single phrase listing functions—with no wasted words. However, it lacks front-loaded clarity about the primary purpose, slightly reducing effectiveness despite efficient wording.

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?

For a tool with multiple complex functions (validation, code generation, mocking, etc.), no annotations, no output schema, and a vague description, this is inadequate. The description doesn't explain return values, error conditions, or how the listed capabilities interrelate, leaving significant gaps for agent understanding.

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 the schema documents the single 'params' parameter adequately. The description adds no parameter-specific information beyond what the schema provides, meeting the baseline for high coverage but not compensating with additional semantic context.

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 lists multiple functions (auto-infer schemas, validate, generate TypeScript, mock data, diffs) but doesn't specify a primary verb+resource combination or distinguish from sibling tools. It's vague about what the tool actually does as a cohesive operation rather than just listing capabilities.

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 on when to use this tool versus alternatives is provided. The description doesn't mention any context, prerequisites, or exclusions for usage, leaving the agent with no directional help for tool selection.

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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