create_dataset

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

Annotations already declare this is a non-read-only but non-destructive, closed-world write. The description adds genuinely useful behavior beyond that: paths resolve on the MCP host, folders are recursed, caption files are auto-paired, and transfer goes over the UI's API so it works cross-machine. It omits what happens on duplicate names or partial upload failures, keeping it below a 5.

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 action in the first clause, then supporting mechanics in a tight second paragraph. Efficient overall, though the backtick-only parameter mention without explanation costs a little clarity for little gain.

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 an output schema present, return values need no explanation, and the description adequately covers the mutation's mechanics and environment assumptions. The main remaining gap is the unexplained caption_ext parameter and duplicate-name behavior for a tool that can append to existing datasets.

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 0%, so the description must carry parameter meaning. It does well for `paths` (files vs. folders, recursion, caption pairing), but `caption_ext` is never explained — the example 'photo1.txt' hints at the default only indirectly — and `name` is left undefined as to uniqueness or reuse semantics.

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 ('Create a dataset ... by uploading local files') and adds the important nuance that it can also append to an existing dataset. That distinguishes it from list_datasets, set_captions, and the job-creation siblings without needing the 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?

Implicit usage is clear: call this when you need a dataset materialized from local files. However, it never states when to prefer a sibling (e.g., set_captions or auto_caption_dataset after creation) or what happens if the name collides with an existing dataset, so routing is left partly to inference.

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