mcp-server-playground

Describe table

describe_table

Read-only

Get column definitions and three sample rows for any table by providing its name. Quickly understand table structure and sample data.

Instructions

Show the column definitions and three sample rows for one table.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table": "<table>"
    },
    "name": "describe_table"
  }
}

Input Schema

Name	Required	Description	Default
`table`	Yes	Table name, e.g. "orders". Use list_tables to discover valid names.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 5, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The annotations already declare readOnlyHint=true, and the description aligns with this by using 'Show'. It adds a specific behavioral detail—returning three sample rows—which goes beyond the annotation and helps the agent set expectations. No contradictions or hidden side effects are implied.

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, front-loaded sentence: 'Show the column definitions and three sample rows for one table.' It contains zero filler and immediately conveys the action, scope, and output format.

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 read-only tool with one well-documented parameter and safety annotations, the description fully covers the essential behavior: column definitions and sample rows. It's complete without needing to explain return values in detail, and the absence of an output schema is compensated by the description's clarity.

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 coverage is 100%, with the 'table' parameter having a helpful description including an example and a reference to list_tables. The tool description adds no further parameter information, but the schema already carries the burden, so the baseline of 3 is appropriate.

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 uses the specific verb 'Show' and identifies the resource as 'column definitions and three sample rows for one table', making the tool's function unambiguous. This clearly distinguishes it from sibling tools like list_tables, which lists table names, and the various search/query tools.

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?

While the description doesn't explicitly state 'when to use' or name alternatives, the context is clear: to inspect a table's structure. The parameter description adds useful guidance by recommending list_tables to discover valid names, providing a natural workflow. No competing sibling exists, so no exclusions are needed.

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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