Upload training assets

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

No annotations, so the description carries full burden. It usefully discloses the accepted-vs-failed reporting behavior and accepted source types, which is genuine context. It omits permissions, per-file size limits, and rate constraints, so coverage of behavioral traits is partial.

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?

Front-loaded with the verb and kept to one dense sentence plus a short one, with every clause (formats, caption pairing, dataset modes, path types) doing work. The opening sentence is long but not padded.

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 multi-mode file-upload tool with no output schema and no annotations, the description covers inputs, accepted formats, target-dataset selection, and the shape of the result (what was accepted/failed and why). Missing only minor operational details such as auth and file-size limits.

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 all three parameters are already documented with the dataset_id/name relationship, the caption-pairing rule, and the 100-image cap. The description mostly restates this framing rather than adding syntax or format details beyond the schema, 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 (Upload) and resource (training assets into a dataset), and enumerates accepted file types. It is unmistakably distinct from the generation/editing siblings, though it never names an alternative, so no explicit sibling differentiation.

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?

Explains the two upload modes (existing dataset via dataset_id vs new one created from name) and supported sources (local paths or public https URLs), implying when to use each. However there is no guidance on when to reach for this versus ideogram_datasets or ideogram_train, and no prerequisites are stated.

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