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chncaesar

pg-semantic-mcp

describe_table

Retrieve column metadata for any PostgreSQL table. Inspect column names, data types, and schema details to understand table structure.

Instructions

Return column metadata for a table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable name in "schema.table" format (e.g. "ods.bd_customer") or bare table name (defaults to "public"/"dbo" schema).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It simply states 'Return column metadata' without mentioning whether the operation is safe/read-only, whether it requires special permissions, how errors are handled, or any side effects. The minimal description leaves behavioral expectations unclear.

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, direct sentence that immediately conveys the tool's purpose. There is no wasted words or unnecessary repetition, front-loading the core action.

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

Completeness3/5

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

The tool is simple, has a fully documented parameter schema, and an output schema exists, so return values need not be explained. However, the description lacks any usage context or mention of when to choose this tool over siblings. It is minimally sufficient but leaves the agent without guidance on applicability.

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 description coverage is 100%: the 'table' parameter already has a detailed description explaining schema.table format and default schema behavior. The tool description adds no additional parameter semantics, so the baseline of 3 applies.

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 clearly states the tool's function: 'Return column metadata for a table.' It uses a specific verb ('return') and resource ('column metadata'), and it is distinct from sibling tools like list_tables (which lists tables) and sample_data (which returns data rows).

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or reference sibling tools. There is no explicit context for choosing describe_table over list_tables or search_schema.

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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