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

With no annotations, the description carries the full burden and does disclose the return payload in useful detail (column metadata, row count, exactly 5 sample rows), which is the key behavioral fact since there is no output schema. It never states this is a read-only operation or discusses permissions/cross-workspace visibility, so it falls short of fully self-describing.

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?

Two sentences: the return contents are front-loaded in a compact parenthetical, followed by the actionable precondition. No filler or restatement of the tool name.

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?

No output schema exists, and the description compensates by specifying precisely what comes back, including the sample-row cap of 5. Parameters are fully documented in-schema, so nothing an agent needs to call this correctly is missing.

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 100% and both parameters (table, workspace) already document themselves including the list_workspaces/list_data_tables pointers, so baseline 3 applies. The description adds no additional meaning about parameter usage or format beyond what the schema provides.

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 names a specific resource (a data table) and enumerates exactly what is returned: columns with name/type/select options/unique flag/row-title flag, plus row count and 5 sample rows. That is materially more specific than the name alone. It stops short of naming sibling tools like query_rows or list_data_tables, so an agent must infer the boundary from the 'sample rows' framing.

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?

'Read this before adding or changing rows so values fit the columns' gives an explicit usage trigger tied to the write tools (add_rows, update_rows, upsert_rows). It does not state when not to use it, e.g. when to reach for query_rows to actually read full row data instead of the 5-row sample.

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