get_metric_dataset

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

No annotations are provided, so the description must fully disclose behavioral traits. It implies a read operation (name starts with 'get') but uses 'Run', which could indicate execution. It fails to mention side effects, permissions, idempotency, or error behavior.

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 sentence, making it concise, but it is overly sparse for a tool with a complex nested input. It lacks structure and essential details, falling short of being appropriately informative.

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 output schema, annotations, and parameter details, the description is incomplete. It does not explain return values, the expected format of the metric definition, or any constraints, making it insufficient for an agent to use correctly.

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% for the nested 'definition' parameter. The description only labels it as a 'metric definition' without explaining its structure or required fields. This leaves the agent uncertain about how to construct the input.

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 tool's action: 'Run a metric definition as a dataset query in Metabase.' It specifies the verb ('Run'), the resource ('metric definition'), and the context ('dataset query'), effectively distinguishing it from sibling tools like 'get_metric' which retrieves definitions.

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 such as 'execute_query' or 'get_metric'. It lacks context about prerequisites, common use cases, or 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.