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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds the meaningful constraint that results are capped at 100 columns and that a version is returned. It omits any auth/permission notes, so with annotations doing most work a 3 is fair.

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?

A single tight sentence with the core action front-loaded and no filler. Every clause carries information (scope, cap, purpose).

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?

An output schema exists, so return values need not be explained. However, with 0% parameter documentation and no explicit guidance on the nullable table/version/workspace_id arguments, the definition is only minimally complete for a tool whose main job is to be called with the right identifying arguments.

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 all four parameters (table, version, dataset_id, workspace_id) rely on the description. It only loosely gestures at 'table' and 'version' and says nothing about dataset_id, workspace_id, or the nullable defaults, which is a substantial gap for a 4-param tool.

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 verb (read) and resource (one table's schema and version), with a useful scope qualifier of up to 100 columns. It is distinguishable from list_datasets, browse_dataset_rows and query_dataset, though it doesn't name those siblings explicitly.

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 phrase 'for subsequent row queries' implies this is a precursor to query_dataset/browse_dataset_rows, giving some context. However it never explicitly states when to use this instead of those tools, nor any prerequisites or exclusions, leaving usage largely to inference.

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