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

With no annotations provided, the description carries the behavioral disclosure burden. It explains important behavior: dimensions up to 64 options are listed inline with labels, while larger ones only report counts and require search_options. This gives an agent realistic expectations about output size and follow-up actions, even if it does not discuss auth, caching, or failure modes.

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 with no filler. The first sentence front-loads the core output contents, and the second efficiently explains the threshold behavior and the search_options alternative. 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?

For a one-parameter describe operation with an output schema, the description is nearly complete. It tells the agent what to expect, how large option sets are handled, and where to go for more. It could explicitly state that this is a metadata-only operation, but the output and sibling context make that reasonably clear.

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 100%, so the single 'table' parameter is already documented as a Dataflow id in the input schema. The tool description does not add further meaning to the parameter, which is acceptable because the schema handles it. Baseline 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 identifies what the tool returns: a table's dimensions in key order, coverage dates, and observed options. It also distinguishes itself from search_options by noting that larger option sets are handled separately. It lacks an explicit action verb in the description, but the title and name supply the 'describe' action.

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 implies when to use this tool—when you need table structure and dimensions—and points to search_options for searching large option sets. However, it does not explicitly state when to use describe_table versus other siblings like search_tables, get_data, or execute. The usage context is reasonably clear but left mostly to inference.

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