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SurajKGoyal

amnesic

by SurajKGoyal
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

db_discover_relationships

Discover all foreign key relationships in your database and persist them to the local graph for efficient JOIN query planning.

Instructions

Discover all foreign key relationships in the database and save them to the graph.

Runs driver-specific FK introspection queries against the live database and
persists results to the local KnowledgeStore. Run once per database; re-run
after schema changes. After discovery, use db_get_relationships to navigate
the graph when planning complex JOIN queries.

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

Returns:
    {connection, discovered: count, relationships: [{from_table, from_column, to_table, to_column}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionNo

Tool Definition Quality

A4.8/5.0
Behavior4/5

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

With no annotations, the description fully discloses behavior: runs driver-specific FK introspection queries, persists to KnowledgeStore, and implies potential impacts (live database query). Could mention performance implications or permissions, but still transparent.

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 a short summary, usage guidelines, and listed args/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?

Completely covers the tool's lifecycle, return format, and relationship to sibling tools. No gaps given the simple parameter set and no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description includes an Args section explaining the single parameter 'connection', its meaning, and default behavior ('Defaults to first defined'), adding value beyond the schema which only shows default null.

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 discovers all foreign key relationships and saves them to the graph. It uses specific verbs (discover, save) and resources (foreign key relationships, database, graph), and distinguishes from sibling tool db_get_relationships.

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

Usage Guidelines5/5

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

Explicitly states when to use ('Run once per database; re-run after schema changes') and when not, by directing to use db_get_relationships for navigation after discovery.

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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