describe_warehouse

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

With no annotations, the description carries the burden for behavioral disclosure. It usefully adds that the tool returns 'relevant data-dictionary notes (gotchas, join keys, conventions)', and hints at read-only behavior by using 'list' and 'show'. However, it does not mention any side effects, error handling, or permission requirements, leaving some ambiguity for a tool that lacks annotation support.

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 a single, compact sentence that is plainly front-loaded with the main actions. It avoids filler and efficiently conveys the two usage modes in minimal words.

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 low-complexity tool with one parameter and no output schema, the description covers the essential behavior and returns (list of tables/views or columns+notes). It does not detail the output structure, but that is likely self-evident from the 'columns' and 'notes' phrasing. Minor gaps like error conditions are acceptable for this scope.

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?

The schema has a single 'table' parameter with no description, so the description must compensate. It does so by explaining the no-arg behavior (list tables/views) and the arg behavior (show columns for that table). This adds meaningful semantics beyond the bare schema, though it does not specify the exact format of expected table names.

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 opens with a specific verb ('List') and clearly identifies the resource ('tables/views' and 'one table's columns'). It actively distinguishes two modes of operation and the inclusion of 'data-dictionary notes' further clarifies the tool's unique purpose among siblings like query_warehouse.

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 makes the usage context explicit: call with no argument to list tables/views, or with a table argument to show columns. It does not explicitly contrast with alternatives (e.g., query_warehouse), but the distinct purpose is clear enough to guide selection.

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