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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds that the output is a download URL rather than inline data, but says nothing about size limits, async behavior, or link expiry that would matter for an export tool.

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?

One compact sentence that front-loads the return value (CSV download URL) and appends the optional filters. No filler, nothing restated redundantly.

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?

With annotations covering safety and a 100%-covered schema, the remaining burden is the return value, which the description handles by naming the CSV download URL. It is nearly complete for this tool, missing only edge details like large-export handling, which the lack of an output schema does not require it to cover.

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 the schema already documents all three parameters with examples, setting a baseline of 3. The description adds meaning above that baseline by tying the dimension keys (dim1…dim8) back to inspect_dataset, telling the agent where the filter vocabulary comes from.

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 ('Return a CSV download URL for a dataset') plus the filtering scope. This cleanly distinguishes it from siblings like get_dataset (fetch data) and inspect_dataset (inspect structure), which a sibling-naming reference to inspect_dataset reinforces.

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 mention of 'dim1…dim8 from inspect_dataset' implies a prerequisite workflow (inspect before exporting) but never says so explicitly. There is no stated when-to-use-vs-alternative against get_dataset or search_datasets, leaving routing to inference.

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