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 of behavioral disclosure. While it mentions the optional schema filtering, it doesn't describe what the tool returns (e.g., table names, counts, or metadata), whether it's paginated, if it requires specific permissions, or any performance considerations. For a read operation in a database context, this leaves significant gaps in understanding how the tool behaves.

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, efficient sentence that front-loads the core purpose ('Lists tables in an MSSQL Database') and adds the optional filtering detail. There's no wasted verbiage or redundancy. However, it could be slightly improved by structuring it as two sentences for better readability (e.g., separating the base action from the filtering option).

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 lack of annotations and output schema, the description is incomplete for a database tool. It doesn't explain what information is returned (e.g., table names, schemas, row counts), how results are formatted, or any constraints (e.g., permission requirements, database connection details). For a tool that interacts with MSSQL, more context is needed to use it effectively without trial and error.

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 input schema has 100% description coverage, with the 'schemas' parameter clearly documented as optional for filtering. The description adds marginal value by restating this filtering capability ('or list tables in specific schemas'), but doesn't provide additional context like schema naming conventions, default behavior when omitted, or examples. With high schema coverage, the baseline score 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 action ('Lists tables') and resource ('in an MSSQL Database'), making the purpose immediately understandable. It also specifies the optional filtering capability ('or list tables in specific schemas'), which adds useful detail. However, it doesn't explicitly differentiate this tool from its siblings like 'describe_table' or 'get_table_ddl', which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives. With siblings like 'describe_table' (for detailed table info) and 'get_table_ddl' (for schema definitions), the description fails to clarify that this tool is for listing table names only, not for retrieving detailed metadata or definitions. There's no mention of prerequisites, limitations, or typical use cases.

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