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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds genuine non-schema context: the call is free, and the operator's private projects surface 'only with your key,' which is real authorization/scope information. It also clarifies the append-only, versioned nature of the underlying data, though return format and listing limits are not described.

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 sentences, each earning its place: returned fields first, a compact conceptual definition, then usage and cost/scope notes. Front-loaded and free of 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, the description usefully enumerates the surfaced fields and covers cost and key-scoped visibility. The only mild gap is that listing behavior (pagination, result caps, sort order) is not mentioned, which matters for a discovery/list endpoint.

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 100% and the single query parameter is fully documented in the schema as a substring filter on slug or title. The description adds no parameter-level detail beyond what the schema states, so the baseline of 3 applies.

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 states a specific verb (list/find) and resource (dataset projects on WITAN), enumerates the exact fields returned (slug, title, access, visibility, latest version, record count), and defines what a dataset is. It also implicitly separates this discovery tool from siblings like dataset_info, read_dataset, and contribute_records by framing it as the way to find data before reading or contributing.

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?

It gives a clear use context: 'Use it to find data by topic before reading or contributing,' which tells the agent where this fits in the workflow. It does not explicitly name alternative sibling tools (e.g. dataset_info for known slugs) or state when not to use it, so it stops short of full routing guidance.

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