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 behavioral burden. It implies a read-only listing, but never states that it is non-mutating, what permissions are needed, or what the return shape is (e.g. bare table names vs. rows). For a zero-param introspection tool the risk is low, but the disclosure is minimal.

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 that wastes no words. It is appropriately sized for a trivial listing tool, though the database qualifier could be trimmed or expanded to name the actual DB.

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 zero-param, no-output-schema listing tool the description is nearly sufficient, but it leaves the return format unspecified (names only? schema-qualified?) and offers no routing cues to the sibling describe_table, which an agent would likely need right after listing tables.

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, so there are no parameter semantics to document; the baseline for a parameterless tool is 4.

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 ('all tables') with a clear scope ('in the SQLite database'), so the agent knows exactly what it returns. However, it does not differentiate itself from the sibling describe_table or query_database, which could also surface table information.

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 gives no when-to-use guidance, no prerequisites, and never mentions alternatives such as describe_table for column-level detail or query_database for data retrieval. The agent must infer the appropriate context entirely.

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