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victor-velazquez-ai

Enterprise MCP Template

get_record_schema

Retrieve the schema and structure for record payloads to understand expected data formats and construct correct payloads for AI client interactions.

Instructions

Get the schema/structure for record payloads. Returns documentation about expected payload formats.

TEMPLATE: Replace with your domain-specific schema documentation. This helps AI clients construct correct payloads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler implementation of the tool 'get_record_schema' which returns the documentation for record payloads.
    @mcp.tool()
    def get_record_schema() -> Dict[str, Any]:
        """
        Get the schema/structure for record payloads.
        Returns documentation about expected payload formats.
        
        TEMPLATE: Replace with your domain-specific schema documentation.
        This helps AI clients construct correct payloads.
        """
        return {
            "description": "Record payload schema for {{PROJECT_NAME}}",
            "note": "TEMPLATE: Replace this with your actual record schema",
            "required_fields": {
                "entity": {
                    "type": "object",
                    "description": "Reference to the owning entity",
                    "example": {"id": "123"},
                },
            },
            "optional_fields": {
                "memo": {"type": "string", "description": "Description"},
                "date": {"type": "string", "format": "YYYY-MM-DD"},
            },
            "example": {
                "memo": "Example record",
                "entity": {"id": "123"},
                "date": "2026-01-15",
            },
        }
Behavior3/5

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 correctly indicates this is a read operation that returns documentation, but lacks details on the format of returned schema (JSON Schema?, OpenAPI?), caching behavior, or whether the schema is static or dynamic.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description contains obvious template placeholder text ('TEMPLATE: Replace with your domain-specific schema documentation') that serves no purpose for the AI agent and indicates an unfinished implementation. This meta-text wastes tokens and creates confusion.

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?

While the context signals indicate an output schema exists (reducing the description's burden to explain return values), the presence of template text suggests the tool definition is incomplete. For a schema introspection tool with no parameters, the description should specify what format the schema documentation takes (e.g., JSON Schema, field listings).

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?

The tool has zero parameters and the schema correctly reflects this with 'additionalProperties: false'. Per evaluation guidelines, zero-parameter tools receive a baseline score of 4 since there are no parameter semantics to describe beyond what the schema already provides.

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 first two sentences clearly state the tool retrieves schema/structure information for record payloads. However, the inclusion of 'TEMPLATE: Replace with your domain-specific schema documentation' indicates placeholder content that pollutes the description and creates ambiguity about whether this is a fully implemented tool or a stub.

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 provides implied usage guidance by stating it 'helps AI clients construct correct payloads,' suggesting it should be used when preparing data for create/update operations. However, it lacks explicit guidance on when to prefer this over siblings (e.g., 'Call this before create_record').

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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