Skip to main content
Glama

get_schema_doc

Retrieve detailed schema documentation for a named data model, listing properties, types, required fields, and enums to understand its structure.

Instructions

Obtiene la definición de un modelo de datos o schema dereferenciado (propiedades, tipos, campos obligatorios y enums).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specIdNoID o nombre de la especificación a consultar (opcional).
schemaNameYesNombre del schema o componente (ej. "LoginRequestDto", "MemberBalanceResponseDto").
Behavior3/5

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

With no annotations provided, the description carries the behavioral burden. It discloses that the schema is dereferenced and enumerates the returned content (properties, types, required fields, enums), which is useful. It does not mention error cases, optional specId handling, or any resolution side effects, leaving moderate ambiguity.

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?

A single, focused sentence that front-loads the main purpose and appends the relevant definition details. No filler or redundant content. It is compact without losing the essential scope.

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 simple retrieval tool, the description gives the core information: what is fetched and what the return content includes. There is no output schema, so a bit more detail on the response format or specId behavior would help, but the description is substantially sufficient for an agent to decide to invoke it.

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 documents both parameters fully (coverage 100%), so baseline 3 applies. The description adds little about parameter semantics beyond implying schemaName is the thing to look up; no extra detail about how specId interacts is provided.

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?

The description clearly identifies the resource (schema/data model definition) and what the tool returns (properties, types, required fields, enums). It does not explicitly differentiate from siblings like get_endpoint_doc or get_security_schemes, but the resource type is distinct enough that an agent can infer its purpose.

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?

Usage context is implied: use this tool when you need a schema definition (e.g., 'LoginRequestDto' or 'MemberBalanceResponseDto'). There is no explicit guidance about when not to use it or which sibling alternative to prefer, but the purpose itself gives reasonable inference.

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/manuelperezg/mcp-docu-mid'

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