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

Annotations already disclose readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the description does not need to restate safety. It adds contextual scope ('7 ISOs') and the workflow (produces dataset_id), but it does not disclose return format, result count, pagination, or any rate limits. This is adequate but with clear gaps.

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?

Two short sentences carry all the essential information: purpose, scope, coupling to gridstatus_query, and a compact executable example. The result is appropriately front-loaded and every sentence earns its place.

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 2-parameter, read-only, no-output-schema tool, the description is mostly complete: it states a specific discovery scope, names the primary use case, and gives a concrete example. The one gap is that it never mentions the shape of the return value (e.g., a list of records containing dataset_id), which is left to the agent to infer. This modest gap prevents a 5.

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 coverage is 100% with both parameters (filter, _apiKey) having full descriptions, so the baseline is 3. The description's example duplicates the schema's example for filter and does not introduce new meaning beyond what the schema already declares. No extra semantical value is added.

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 uses a specific verb-resource pair ('List/search US grid datasets') and immediately limits the scope to 7 ISOs and dataset categories like LMP and fuel mix. It explicitly connects to the sibling tool gridstatus_query by stating that its purpose is to discover the dataset_id to pass there, so an agent can distinguish it from gridstatus_query or gridstatus_latest.

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?

"Use this to discover the exact dataset_id to pass to gridstatus_query" is an explicit when-to-use instruction that links to a named sibling. The description also provides an example of the call pattern, implying that the tool is for discovery before querying real-time data. This is as explicit as the get_calls calibration exemplar.

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