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

Annotations already declare the tool is read-only, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds useful behavioral context by disclosing the inclusion of licences and explicit coverage limitations, without contradicting 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 a single, front-loaded sentence with no wasted words. The parenthetical list of limitations is dense but every item directly serves scope clarification.

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 an output schema available, the description need not explain return values. For a zero-parameter informational tool, it adequately covers sources, licences, and limitations, giving the agent enough to know what this tool does and does not provide.

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 parameter semantics are not applicable and the baseline is 4. No parameter documentation is needed.

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 identifies the resource: data sources, licences, and coverage limitations behind DwellDelta's figures. It distinguishes itself from data-returning siblings by focusing on provenance and scope, though it uses a noun phrase rather than an explicit verb.

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 'what it cannot answer' list gives strong negative guidance, effectively telling the agent when not to expect answers from this tool. However, it does not explicitly name sibling alternatives or state a positive 'use this when' condition.

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