postgresql-mcp

describe_table

Retrieve a PostgreSQL table's schema: columns, data types, nullability, and default values. Useful for understanding table structure before writing queries.

Instructions

Describe table structure (columns, types, nullability, default).

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_name": "<table_name>"
    },
    "name": "describe_table"
  }
}

Input Schema

Name	Required	Description	Default
`table_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. 'Describe table structure' strongly implies a read-only metadata operation with no side effects, which covers the most important behavioral trait. However, it does not explicitly state read-only semantics, error behavior for missing tables, or any permission requirements. This is adequate but not thorough.

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 concise sentence that front-loads the core action ('Describe table structure') and immediately specifies the returned components. There is no filler or redundant restatement of the tool name.

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 read-only metadata tool with one obvious parameter, the description covers the essentials: what the tool returns and the target resource. The presence of an output schema reduces the need to document return values, though the description still lists them. It is missing explicit guidance on error behavior and permissions, but for this tool's simplicity the description is nearly complete.

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 schema has zero description coverage, and the description does not explicitly explain the table_name parameter. However, the parameter is self-evident given the tool name and the phrase 'Describe table structure', which implies the named table is the target. The description adds minimal meaning beyond the schema and does not fully compensate for the lack of schema documentation, but the single parameter poses little ambiguity.

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 a specific verb ('Describe') and a concrete resource ('table structure'), and enumerates the relevant aspects ('columns, types, nullability, default'). This clearly distinguishes it from siblings like create_table and list_tables, which handle creation and enumeration rather than schema introspection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to use this tool versus its siblings. The description only states what the tool does; it does not mention that list_tables is for enumerating tables or that execute_sql is for arbitrary queries. Usage context is entirely implied rather than stated.

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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