ingest_datasource_models

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

With no annotations, the description carries the behavioral disclosure burden. It clearly states idempotence, that re-runs are additive only, that existing definitions are never overwritten, and that the result includes pending validate_models deletes. This is substantial transparency for a mutating tool, though it does not cover failure modes or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and the crucial idempotence guarantee, followed by the necessary parameter documentation. The wording around 'pending validate_models deletes' is slightly awkward, but every sentence earns its place given the lack of schema descriptions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with five parameters, mutual exclusions, and a mutating/additive behavior, the description provides enough context to invoke it correctly: source datasource, table filtering, schema selection, and the additive result. It does not explain return structure in detail, but an output schema exists and the behavioral guarantee is clear.

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

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

Schema description coverage is 0%, so the description must compensate with parameter details. The Args section explains each parameter, gives examples, defines empty-string behavior, and documents mutual exclusivity among schema_name, schemas, and all_schemas. This fully compensates for the missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Auto-discover tables in a database') and a clear outcome ('create / additively update semantic models'). It clearly differentiates from sibling tools like create_model and edit_model by focusing on automatic discovery rather than manual construction.

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

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

The description gives clear context: it operates on an existing datasource from list_datasources and is additive/idempotent, so it is safe to re-run. It does not explicitly enumerate when to choose this over create_model/edit_model, but the auto-discovery language makes the intended use case clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.