dataset_series

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety behavior is covered. The description adds useful context about the metrics returned (days, rows, size), but does not discuss pagination despite the limit parameter, authentication needs, or other behavioral details.

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 description is a single efficient sentence with the core purpose front-loaded. It contains no filler, though it is sparse enough that it leaves key parameter meaning unaddressed.

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?

An output schema exists and annotations cover read-only/open-world behavior, but the tool has three parameters with zero schema descriptions and the description does not explain query or limit. For an agent to invoke it confidently, more parameter and routing guidance is needed.

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 0%, so the description must compensate for undocumented parameters. It only indirectly identifies dataset_id via 'in one dataset' and examples, and says nothing about the query or limit parameters.

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?

The description clearly states that the tool lists series with files in one dataset, with examples like book_l2 and trades, and mentions returned metrics (days, rows, size). It is specific about the resource and scope but does not differentiate itself from nearby tools such as get_series or list_files.

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?

There is no explicit guidance on when to use this tool versus alternatives like get_series, search, or list_files. The dataset-scoped purpose implies usage, but no exclusions, prerequisites, or alternative-selection criteria are given.

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