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amnesic

amnesic

by SurajKGoyal
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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db_list_tables

List all known tables for a database connection, including descriptions and column counts from the knowledge store.

Instructions

List all known tables for a connection, with descriptions and column counts.

Tables appear once they have been fetched via db_get_schema or annotated via
db_annotate. Descriptions come from the knowledge store — richer than raw
INFORMATION_SCHEMA.

Args:
    connection: Connection name. Defaults to first defined.

Returns:
    {connection, database, tables: [{table_fqn, description, aliases, column_count}]}

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "db_list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
connectionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, so description carries the burden. It discloses that descriptions come from the knowledge store (richer than raw schema) and that tables are only shown if known. No destructive behavior implied. Return format is given.

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?

Well-structured with clear purpose, behavioral notes, Args, and Returns. Every sentence adds value, no fluff.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description covers all essential aspects: purpose, prerequisites, return format, and parameter behavior. Complete for its complexity.

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?

Single optional parameter 'connection' is documented with default behavior ('Defaults to first defined'), adding useful meaning beyond the schema type and default.

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?

Description clearly states it lists all known tables for a connection, including descriptions and column counts. It distinguishes itself from siblings like db_get_schema (which fetches schema) and db_annotate (which annotates) by noting that tables appear only after those actions.

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?

Provides context by explaining that tables appear only after being fetched or annotated, guiding the user on prerequisites. However, it does not explicitly state when to use or not use this tool versus 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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