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@yawlabs/postgres-mcp

by YawLabs

pg_list_tables

Read-onlyIdempotent

List tables and views in a PostgreSQL schema, returning name, type, and estimated row count. Supports pagination for large schemas.

Instructions

List tables (and optionally views) in a schema. Returns name, type (table/view/materialized view/foreign), and estimated row count (from reltuples; null = no ANALYZE yet on PG 14+; 0 may mean empty or unanalyzed on PG <= 13). Paginate via limit/offset on very large schemas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return (default 500, max 10000).
offsetNoRows to skip for pagination (default 0).
schemaNoSchema name (defaults to 'public').public
includeViewsNoIf true, include views and materialized views.
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds critical nuance about row count semantics (null vs 0 meaning varies by PG version) and the effect of includeViews parameter, going beyond what annotations provide.

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?

Two well-structured sentences with no superfluous text. First sentence defines purpose and return fields, second covers pagination. Every word earns its place.

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 read-only listing tool with no output schema, the description adequately covers return fields, pagination, schema parameter, and includeViews. Annotations provide safety guarantees, and the description fills behavioral gaps.

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?

Schema coverage is 100%, so description doesn't need to explain parameters. However, it adds value by clarifying the row count field's behavior and the purpose of limit/offset for schema browsing, enhancing understanding.

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 'List tables (and optionally views) in a schema' with specific resource (tables/views), verb (list), and scope (schema). It distinguishes from siblings like pg_list_views which focuses solely on views.

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?

Mentions pagination via limit/offset for very large schemas, providing clear usage context. However, does not explicitly state when not to use this tool or name alternatives.

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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