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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds behavioral context by specifying exactly what data dimensions the tool exposes: per-source counts, open sales, retained comps, and last-refresh timestamps. This tells the agent what to expect from the tool beyond the structured 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 with no wasted words. It front-loads the main subject and immediately lists the key content categories, followed by a clear, actionable purpose. Every sentence earns its place, and the structure makes scanning easy.

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, read-only coverage tool, the description is complete. It states what the tool reports, that the data is per-source and current, and how the agent should use it. With no output schema, the description sufficiently covers return value semantics and selection criteria, leaving no critical gap for correct invocation.

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, so there is no parameter semantic burden for the description to bear. An empty input schema with 100% coverage means nothing is undocumented. The baseline of 4 applies, and the description appropriately focuses on output semantics rather than input details.

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 defines the tool as a coverage/status report for US auctions, enumerating the key metrics returned: active lot counts, open sale counts, retained sold comps, and source refresh times. This distinguishes it from sibling tools like us_auctions_search or us_auctions_sold_comps, which provide actual auction data rather than an overview. The purpose is immediately obvious despite not using a verb like 'get' or 'list'.

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 the tool: 'Use to gauge breadth and freshness before relying on the data.' This provides clear context for the agent—checking data coverage and recency prior to acting on auction data. It does not explicitly name alternatives or exclusion criteria, but the use case is specific enough to avoid confusion with sibling tools.

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