Skip to main content
Glama

json_schema

Generate TypeScript schema definitions from JSON files or URLs to validate data structures and reduce context size in LLM applications.

Instructions

Generate TypeScript schema for a JSON file or remote JSON URL. Provide the file path or HTTP/HTTPS URL as the only parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesJSON file path (local) or HTTP/HTTPS URL to generate schema from
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool generates a TypeScript schema, but does not describe how it handles errors (e.g., invalid JSON, network issues), what the output format looks like, or any performance or security considerations, leaving significant gaps for a tool that processes external data.

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 a single, efficient sentence that is front-loaded with the core purpose and includes essential usage details without any redundant or unnecessary information, making it highly concise and well-structured.

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?

Given the tool's complexity (processing external JSON data), lack of annotations, and no output schema, the description is incomplete. It fails to address critical aspects such as error handling, output format, or security implications, which are necessary for safe and effective use by an AI agent.

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 input schema already fully documents the single parameter. The description adds minimal value by restating the parameter's purpose ('file path or HTTP/HTTPS URL') without providing additional syntax, format details, or constraints beyond what the schema specifies.

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 specific action ('Generate TypeScript schema') and the resource ('JSON file or remote JSON URL'), distinguishing it from sibling tools like json_dry_run and json_filter by focusing on schema generation rather than validation or filtering operations.

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 usage by specifying the input type ('JSON file or remote JSON URL'), but it does not explicitly state when to use this tool versus alternatives like json_dry_run or json_filter, nor does it provide any exclusions or prerequisites for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kehvinbehvin/json-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server