demo.list_tables

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

No annotations are provided, so the description carries the full burden. 'List' strongly implies a safe read-only operation and it discloses the return scope (tables plus their columns), but it says nothing about result size, ordering, or whether column detail is names only.

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?

A single front-loaded sentence with no filler; the resource and scope are stated immediately and nothing redundant follows.

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 trivial zero-parameter tool this is nearly sufficient, but with no output schema the description should clarify the shape of what comes back — e.g. whether columns are names, types, or full definitions. As written, 'their columns' is ambiguous.

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 tool takes zero parameters and the description correctly implies no filtering or scoping inputs are accepted, so there is no parameter meaning left to document. Baseline of 4 applies for a parameterless tool.

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?

States a specific verb (list) and resource (tables and their columns) scoped to the demo database, so an agent knows exactly what it returns. It does not explicitly name or contrast with the siblings demo.describe_table and demo.query, but the 'all tables' scope makes its role inferable.

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?

There is no explicit when-to-use guidance or mention of alternatives. The breadth implied by 'all tables' hints that this is the inventory/discovery entry point before drilling into a single table, which is adequate but left entirely to inference.

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