list_datasets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds the 'offline snapshot or live' distinction as part of the output, but does not discuss performance, pagination, or any other behavioral nuance. Given the strong annotation coverage, a 3 is appropriate – the description adds modest context without contradicting the annotations.

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 two sentences, front-loaded with the core function and output fields, followed by usage guidance and alternatives. Every sentence earns its place; there is no fluff or redundancy. It is an exemplary model of conciseness.

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?

For a zero-parameter list tool with an output schema (as signaled by has_output_schema=true), the description fully covers what the tool does, what it returns, how to use it, and when to use alternatives. Nothing an agent needs to call it correctly is missing.

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 has zero parameters, and the schema coverage is 100% (empty schema). Per the rubric, a tool with no parameters gets a baseline of 4. The description does not need to explain parameters because there are none, and it does not introduce any misleading parameter references.

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 opens with a specific verb and resource: 'List every dataset this server can query' and enumerates the returned fields (id, source agency, category, snapshot/live, feature count). It clearly distinguishes itself from sibling tools like describe_dataset, query_dataset, hazards_at_location, and nearest_resources by stating its role as the entry point for dataset discovery.

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 explicitly states when to use this tool ('Start here to find dataset ids for describe_dataset and query_dataset') and when not to ('For hazards or resources at a location, the dedicated tools (hazards_at_location, nearest_resources) are simpler'). It names the alternatives and the conditions that select them, leaving no ambiguity.

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