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

Annotations only declare readOnlyHint=false and destructiveHint=false. The description adds real behavior: content is uploaded to S3, a path is returned in the "path" field, and the hosted server imposes request-size limits. That is exactly the context an agent needs before deciding whether to send data through the 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?

Front-loaded with what it does and what it returns, then the chaining instructions, then the size caveat, then examples. Every part earns its place, though the two worked examples make it longer than strictly necessary for a two-parameter tool.

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?

No output schema exists, but the description covers the return value (the path field) and the exact downstream usage in lexq_simulation_start. Together with the size-limit caveat and format examples, nothing an agent needs in order to call it correctly is missing.

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%, so the baseline is 3. The description still adds value by showing concrete CSV and JSON shapes for the content parameter, which is more informative than the schema's 'CSV or JSON content as string'; the filename parameter is only indirectly referenced via the switch between inline upload and upload_file.

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: upload inline CSV or JSON content as a simulation dataset. It also names the sibling alternative (lexq_dataset_upload_file) and distinguishes the local-server vs hosted-server case, so an agent can tell it apart without opening either schema.

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?

Explicit when-to-use (small datasets, content travels inside the call) and when-not-to-use (larger files, hosted server request-size limits), with named alternatives: lexq_dataset_upload_file on the local server, the CLI, or the console. It also gives the follow-on step for lexq_simulation_start with the exact object shape.

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