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. It states the tool lists tables but doesn't disclose behavioral traits such as whether it requires specific permissions, how it handles large result sets (e.g., pagination), or any rate limits. The description adds minimal context beyond the basic action, leaving gaps in transparency for a read operation.

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 appropriately sized with two sentences and a structured Args/Returns section. The first sentence states the purpose clearly, and the second adds context, but the 'invaluable for AI' phrase is slightly verbose. Overall, it's front-loaded and efficient with minimal waste.

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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the purpose and parameter semantics adequately but lacks behavioral details like permissions or result handling. For a simple list tool, this is minimal viable but could be more informative.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining the 'db_schema' parameter as 'Schema name (default: "public")', clarifying its role and default value, which is not in the schema. With only one parameter, this provides adequate semantics, though it could detail format or constraints further.

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 clearly states the verb ('List') and resource ('all tables present in the connected Cockroach database instance'), making the purpose specific. It distinguishes from siblings like 'list_databases' (which lists databases) and 'list_views' (which lists views), establishing a clear scope for tables only.

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 implies usage by stating it's 'invaluable for AI to understand the database's landscape and identify relevant data sources for a given query,' suggesting context for exploration or query planning. However, it lacks explicit guidance on when to use this tool versus alternatives like 'describe_table' for details or 'list_databases' for broader scope, and no exclusions are provided.

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