lakehouse_list_tables

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

Annotations already mark this as read-only and non-destructive. The description adds valuable behavioral context by disclosing that schema-enabled lakehouses automatically fall back to querying INFORMATION_SCHEMA via the SQL endpoint, which informs the agent about potential implicit behavior and dependencies.

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?

Two sentences, front-loaded with the core action, followed by a relevant behavioral note. There is no redundant text or repetition of schema details.

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 simple read-only list tool with two required parameters and full schema documentation, the description provides sufficient context for correct invocation. It could elaborate on the exact return shape since there is no output schema, but 'list all tables' conveys the essential outcome.

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 100%, with both workspaceId and lakehouseId already described in the schema. The tool description adds no additional parameter-level meaning, so the baseline of 3 applies.

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 verb and resource: 'List all tables in a lakehouse.' This is immediately distinguishable from sibling tools like lakehouse_list (lists lakehouses) and warehouse_list_tables (tables in a warehouse). The additional fallback detail reinforces the purpose without obscuring it.

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 clearly implies when to use this tool—when you need the list of tables in a specific lakehouse. It does not explicitly name alternatives or exclusions, but the resource scope is clear enough that an agent can route correctly among the many sibling list tools.

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