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sap_read_foreign_keys

Retrieve foreign key relationships for any SAP Data Dictionary table to identify related tables and possible joins.

Instructions

Read foreign key relationships for a table from Data Dictionary (DD08L). Shows which tables are related and can be joined.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesData Dictionary table name

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.2

TDQS

A3.6/5.0
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 identifies the source (DD08L) and the outcome, but it does not describe response format, error behavior, permissions needed, or whether the returned relationships include field-level details. This leaves a meaningful gap for a tool whose behavior the agent cannot infer from annotations.

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 two short sentences with no filler. The core action and source are stated up front, and the value ('shows which tables are related and can be joined') follows directly. Every phrase earns its place.

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 one-parameter read-only tool with no output schema, the description is largely complete: it names the input, the source dictionary table, and the resulting information. It would benefit from a brief note on what the output contains (e.g., 'returns related table names and field pairs'), but the current level is adequate for tool selection and invocation.

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 coverage is 100%, including an example ('MARA') and a description ('Data Dictionary table name'), so the schema already documents the only parameter. The description adds a small amount of context by connecting the parameter to foreign-key-relationship lookup, but does not need to compensate for any missing schema information.

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 a specific verb ('Read') and resource ('foreign key relationships for a table from Data Dictionary (DD08L)'). It also explains the practical purpose—showing which tables are related and joinable—which distinguishes it from sibling tools like sap_read_table_structure or sap_infer_joins.

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

Usage Guidelines3/5

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

The description implies the tool is appropriate when an agent needs to discover related tables or determine joinability, but it does not explicitly state when to use this tool versus alternatives such as sap_infer_joins or sap_get_field_metadata. There is no whether-not guidance, so the usage context is only inferred rather than explicit.

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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