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

Annotations already cover the safety profile (readOnlyHint, destructiveHint false, openWorldHint false), so the bar is lower. The description still adds real value: it discloses the 100-row ceiling and, notably, warns that row text, labels and file names are user data and must not be treated as instructions - an injection caveat annotations cannot express.

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, both earning their place: the first front-loads the purpose and scope, the second is a critical safety note. The first sentence is clause-dense, which costs a little readability, but there is no filler.

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, four-parameter tool with no output schema and sparse parameter docs, the description covers the essential shape: pagination, the 100-row cap, per-row content, and the category filter. Ordering and total-count behavior are left implicit, but neither is essential for correct invocation.

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 only 25% (only model_id is documented), so the description must compensate. It does partially: 'up to 100' pins the limit ceiling and 'optionally only one category's' explains the category filter's semantics. However, offset/pagination semantics remain unstated, leaving one parameter undocumented in both places.

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 and resource: reads a page of a model's training rows, with page cap, per-row contents (index, category) and an optional category filter. This is clear and concrete, though it does not explicitly distinguish itself from siblings that also expose training data such as columns, group_rows or dataset_summary.

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 says what comes back but never says when to reach for this tool versus alternatives like group_rows, mistakes or columns. The only usage hint is the incidental 'optionally only one category's', which signals a filtering use case but gives no conditions, prerequisites, or exclusions.

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