Describe a topic in a data source

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

Annotations already mark the operation read-only, idempotent, and non-destructive. The description adds non-obvious behavioral traits: it returns schema, definition, and query instructions but not message rows, and explicitly warns against inferring units from field names. No contradiction with annotations.

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 sentences, front-loaded with the action and purpose. Each sentence adds distinct value: when to use it, what it returns, and a critical data-interpretation warning. There is no filler or repetition.

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?

For a read-only inspection tool, the description covers when to call it, what it returns, and a critical unit-safety warning. An output schema exists to detail return values, but the input parameters are not fully defined, which is a minor completeness gap.

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%, so the description must compensate. It clarifies that 'topic' is a known topic and references describe_data_source for discovery, but it never defines 'path' or the optional 'args' object, leaving required inputs under-specified.

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?

States a specific action—inspect a known topic—and the resource (a topic in a data source). It explicitly distinguishes itself from describe_data_source by pointing to that tool for discovering topic names, so an agent can select the right one.

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?

Explicitly frames usage as a pre-step before writing SQL or event predicates, and directs topic discovery to describe_data_source. It does not explicitly name query_messages as the alternative for retrieving message rows, though the 'without message rows' clause implies that boundary.

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