get_parameters

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

With no annotations, the description carries full burden. It discloses return content, unsupported connections, and error scenarios (not found, unsupported, empty result). It does not mention idempotency or side effects, but for a read operation, transparency is good.

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 well-structured with clear sections (returns, notes, parameters, examples, error handling). It is somewhat lengthy but front-loaded with the main purpose. Every sentence adds value, though it could be slightly more concise without losing clarity.

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 4 parameters (1 required) and output schema existence, the description is thorough: covers purpose, parameters, return fields, usage notes, unsupported scenarios, and error handling. No major gaps remain.

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 coverage is 0%, so the description fully compensates. It explains each parameter: dataset_id (required), workspace_id (optional, My workspace), format (default markdown), detail (default concise). Examples clarify usage, adding meaning beyond schema types.

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 explicitly states the tool's purpose: 'Get parameters defined in a PowerBI dataset.' It is specific with a clear verb and resource, and it distinguishes itself from sibling tools (none of which retrieve parameters).

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 indicates when to use the tool ('Useful for discovering available parameters before querying parameterized datasets') and notes unsupported dataset types. It also provides error handling guidance. However, it does not explicitly contrast with sibling tools, but no direct alternative exists.

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