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Connect Database To RAG Config

lyzr_semantic_model_connect_database

Connect a database to a RAG config to generate documentation for semantic-model tables.

Instructions

Connect a database to a RAG config for semantic-model table documentation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYesDatabase id to connect
rag_config_idYesRAG config id
Behavior3/5

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

Annotations already provide the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), so the bar for additional behavioral disclosure is lower. The description adds minimal behavioral context beyond the connection action—it does not mention effects like whether an existing connection is overwritten or if the operation can be undone. However, given the low complexity, this is adequate but not rich.

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, concise sentence (12 words) that front-loads the action verb and resource. Every word contributes value, and there is no filler or redundancy.

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 tool with two well-documented parameters, no output schema, and existing annotations, the description is nearly complete. It states the exact operation and its purpose. A minor gap is that it does not mention any prerequisites (e.g., that both IDs must reference existing entities), but the low complexity and schema coverage make this a minor omission.

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%, with both parameters ('database_id' and 'rag_config_id') having clear descriptions in the schema. The description does not add significant extra meaning beyond the schema, but it reinforces the purpose by linking the two parameters to the connection action. Baseline 3 is appropriate when the schema carries the parameter semantics.

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 uses a specific verb ('Connect') with a clear object ('a database to a RAG config') and states the purpose ('for semantic-model table documentation'). It clearly distinguishes this from sibling tools like lyzr_semantic_model_list_tables or lyzr_semantic_model_save_documentation by focusing on the connection action.

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?

The description implies when to use the tool by stating its purpose, which is to enable semantic-model table documentation. It does not explicitly mention alternatives or exclusions, but the context is clear that this is the prerequisite step before documentation-related operations. Sibling tools with names like 'list_tables' and 'save_documentation' reinforce this implicit usage context.

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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