query.semantic

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions governance validation, which hints at potential restrictions or errors, but lacks details on execution behavior (e.g., performance, rate limits, error handling, or output format). For a complex query tool with 8 parameters, this is a significant gap in transparency.

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 two sentences, front-loaded with the core purpose and followed by a key behavioral note (governance validation). Every sentence earns its place by providing essential information without redundancy or fluff, making it highly efficient.

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's complexity (8 parameters, no output schema, and no annotations), the description is incomplete. It lacks details on what the query returns, how results are structured, error conditions, or governance specifics. For a data query tool, this leaves critical gaps for an AI agent to understand and use it effectively.

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 schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning beyond the schema, such as examples or usage context for parameters like measures or dimensions. Since the schema does the heavy lifting, 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 ('execute a governed semantic query') and target ('against the data warehouse'), with the verb 'execute' being specific. However, it doesn't differentiate from sibling tools like catalog.describe or catalog.search, which likely serve different purposes (e.g., metadata exploration vs. data querying).

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 mentions that 'queries are validated against governance policies before execution,' which implies a context of compliance or security. However, it provides no explicit guidance on when to use this tool versus alternatives like catalog.describe or catalog.search, nor does it specify prerequisites or exclusions for usage.

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