get_dataset_sources_v1_datasets__provider___dataset__sources_get

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

Without annotations, the description carries the burden and discloses that the output format varies by dataset type (multi-source, aggregator, single-source) and that the endpoint is public. This adds behavioral context beyond just saying 'list sources'.

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 concise: a single introductory line followed by three bullet points for output cases. Every sentence provides unique value without redundancy or filler.

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?

The description covers the return value variations for different dataset types and states the endpoint is public. It is sufficiently complete for a simple two-parameter retrieval tool, though error conditions or edge cases are not mentioned.

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?

The input schema has two parameters (provider, dataset) with 0% description coverage. The tool description only mentions them in the HTTP path without any additional explanation, validation rules, or examples. It adds minimal meaning beyond the schema.

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 it lists all source URLs for a dataset, distinguishing it from sibling tools like get_dataset_by_path or get_dataset_meta. It details three output formats for multi-source, aggregator, and single-source datasets, making the purpose precise.

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 description implies the tool is used to retrieve dataset sources, but it does not specify when to prefer it over other dataset-related tools or when not to use it. No explicit when/when-not guidance or alternatives are provided.

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