list_tables

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

With no annotations provided, the description carries the full burden. It discloses the caching behavior ('Schema is served from cache when available'), which is a useful behavioral trait. But it does not explicitly state that the operation is read-only, nor does it mention potential staleness risks or permissions.

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 two sentences, with the first front-loading the main purpose and the second adding usage context and a caching note. Every word earns its place, with no 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?

Given a single parameter, an output schema, and no annotations, the description covers the purpose, usage context, and a relevant behavioral detail. It does not explicitly mention error conditions or prerequisites beyond the parameter schema, but it is largely complete for a simple list tool.

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 coverage is 100% because the 'connection' parameter has a clear description ('Database alias from connect_database'). The tool description adds little beyond the schema, so the baseline of 3 is appropriate.

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 tool's function with a specific verb and resource: 'List all tables in the connected database with row counts and sizes.' This distinguishes it from sibling tools like describe_table (which focuses on a single table) and profile_table.

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 provides clear context by stating that the editor AI uses this to understand database structure before generating queries. However, it does not explicitly mention alternatives or when not to use this tool, so it stops short of full exclusion guidance.

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