list_tables

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

Without annotations, the description indicates this is a read-only operation listing accessible tables, filtered by user permissions. It does not elaborate on response size, ordering, or potential delays, but the core behavior is clear.

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, informative sentence that concisely states the tool's purpose with no extraneous 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?

Given the simplicity of the tool (no parameters, output schema exists), the description is complete. It specifies the scope (accessible, user tables, configured database) and leaves no critical gaps.

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 has zero parameters, and the schema coverage is 100% (empty schema). The description correctly adds no parameter detail since none exist. According to the baseline for 0 params, a score of 4 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 specifies the action (list), the resource (accessible user tables), and the context (configured MSSQL database). It clearly distinguishes from siblings like describe_table (which describes a single table) and query (which executes queries).

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 implied usage is to discover available tables before using describe_table or query. However, there is no explicit guidance on when it should or should not be used, nor any mention of alternatives beyond the sibling list.

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