List tables

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the flat-array return shape, the table_name schema, and the scoping behavior. It does not explicitly state it is read-only, but 'List' makes this unambiguous enough for a simple discovery tool.

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 purpose, and each sentence adds necessary information: what it lists, what it returns, and how scoping works. No filler or redundancy.

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?

The description is complete for a simple list tool: it explains the return format, scoping, and view inclusion. The absence of an output schema is compensated by the explicit return shape. Minor gaps like explicit error/permission behavior do not materially hurt usability here.

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%, so the baseline is 3. The description adds 'unless overridden', which connects the database/schema parameters to connection-level defaults, but it does not add meaningful detail beyond the schema's property descriptions, especially for include_views.

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 uses a specific verb-resource pair ('List available Snowflake tables (and views)') and clearly distinguishes this from list_databases, list_schemas, and list_warehouses by focusing on tables/views for analytics discovery. It also adds scope context ('Scoped to the connection's database/schema unless overridden'), making the tool's position in the sibling set clear.

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 phrase 'for analytics table discovery' communicates a clear intended usage scenario. It does not explicitly name alternatives or state when not to use the tool, but the context is strong enough for an agent to select it over the database/schema/warehouse listing siblings.

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