Skip to main content
Glama

Get schema detail

get_schema

Retrieve the complete field tree of any data model, including field names, types, required flags, and descriptions. Nested objects and arrays are fully expanded.

Instructions

Returns the field tree of one data model: field names, types, required flags (marked with *) and descriptions. Nested objects and arrays are expanded; recursive refs are shown as → Name. Find names with list_schemas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesExact schema name, e.g. 'OAuth2TokenResponse' or 'CreateOrderRequest'.
Behavior4/5

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

Describes how nested objects and recursive refs are handled, giving clear behavioral insight. No annotations provided, so description carries full burden; could mention read-only nature.

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?

Two sentences with no redundant information. Front-loaded with key output details, efficient and easy to parse.

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

Completeness5/5

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

For a simple tool with one parameter and no output schema, description covers all necessary aspects: purpose, output format, usage hint. Completeness is high given low complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already covers the parameter name well (100% coverage), but description adds valuable examples and context about what the name represents, enhancing meaning.

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?

Description clearly states it returns the field tree of a data model with specifics like types, required flags, and descriptions. Distinguishes itself from siblings like list_schemas by explaining its output granularity.

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?

Explicitly mentions using list_schemas to find schema names, providing clear context for when to use each tool. Lacks explicit when-not or alternatives but is otherwise sufficient.

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/JeongSeongMok/tossinvest-openapi-mcp'

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