list_datasets

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

No annotations exist, so the description carries the full disclosure burden, and it delivers real behavioral context: Fuseki returns 405 rather than 404 for unknown datasets, and endpoint availability varies between assembler-configured and stock configurations. It omits auth or rate-limit expectations, but for a read-only listing operation that is a minor gap.

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?

Three short paragraphs, each front-loaded with its claim and each adding non-redundant information: what is listed, why the 405 signal matters, and why endpoint names are worth reading. No sentence is 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?

With no output schema and no annotations, the description compensates by describing the return content in prose (datasets plus their endpoints) and the diagnostic value of that content. Completeness is good for a zero-parameter listing tool, though a one-line note on how datasets/endpoints appear in the response would close the last gap.

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 tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to disambiguate beyond noting that listing is server-wide rather than scoped.

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 ('List the datasets on this Fuseki server') and adds a distinguishing scope the siblings lack: the endpoints each dataset offers. This differentiates it from dataset_stats, create_dataset, and delete_dataset by outcome rather than name alone.

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?

Gives a concrete trigger condition ('Reach for this first when a call fails with 405') with the reasoning behind it, which is unusually actionable. It does not name an alternative tool or state exclusions, so it stops short of the explicit when/when-not/alternatives bar.

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