Generate more rows

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

Goes well beyond the annotations: discloses billing and settlement behavior, that the generator skips existing rows and may return fewer than requested, the exact progress counters (requested_rows, generated_rows, added_rows, skipped_duplicate_rows), and auto_fill semantics. The return shape (dataset and run) is also stated, which the annotations alone do not convey.

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 key requirements and cost warning are front-loaded, and the worked JSON example is genuinely illustrative rather than filler. Minor waste from echoing the title phrase ('generate more rows') before the real sentence.

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 9-parameter, non-idempotent, open-world mutation with no output schema, the description covers cost, prerequisites, side effects, and return shape. It leaves the budget vs max_credits distinction entirely to the schema, which is a small residual 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 coverage is 100% and the schema already documents every parameter including defaults and the max_credits 422 behavior. The description adds the useful default-source detail for `prompt` (the dataset's last build prompt) and the effect of auto_fill, but largely restates what the structured fields provide, so the baseline 3 applies.

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 ('Generate `count` more rows for a dataset'), making clear this extends an existing dataset rather than creating one. It does not explicitly name the nearest siblings (build_dataset for initial builds, add_dataset_rows for manual rows), so the differentiation is implied rather than stated.

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?

Gives real preconditions: paid operation, call estimate_cost first, dataset needs an index_column set via update_dataset. That is clear context for when to use it, though it stops short of explicit alternatives and when-not conditions relative to add_dataset_rows or build_dataset.

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