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 successfully discloses filtering behavior (excludes hidden tables and system tables prefixed with '$'), but omits safety properties (read-only status), rate limits, or pagination behavior that would be expected for a data retrieval tool.

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?

Three well-structured sentences with zero waste: purpose declaration, behavioral constraints (filtering), and usage guidelines (chaining). Information is front-loaded and every sentence earns its place.

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 has an output schema, the description appropriately does not detail return values. However, with 0% schema coverage on inputs and only two required parameters, the description should have documented the workspace/dataset parameters. Adequate but missing critical input documentation.

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?

Schema description coverage is 0% (no descriptions for workspace_id or dataset_id), and the description fails to compensate by explaining these parameters. While it mentions operating 'in a Power BI dataset' providing loose context, it does not explicitly map to or define the required parameters.

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 provides a specific verb ('List') and resource ('visible tables in a Power BI dataset'), clearly defining the scope. It distinguishes itself from potential siblings by specifying it excludes hidden/internal tables and explicitly mentions it feeds into `list_measures` and `list_columns`.

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?

Provides explicit chaining guidance: 'Use the returned table names in `list_measures`, `list_columns`, and DAX queries', directly referencing sibling tools. Also implies scope limitations (excludes hidden tables), though it could more explicitly state when NOT to use it.

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