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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is low. The description adds genuinely useful behavioral context beyond that: the counts are live and measured from serving views, and they should supersede cached figures, which tells the agent about freshness and authority of the data.

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 sentences, both earning their place: the first defines the payload and its source, the second states the precedence rule. The most decision-relevant content is front-loaded with no 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?

For a zero-parameter tool with an output schema, the description needs only to say what is returned and any caveats; it does both by enumerating the counts and flagging their live/authoritative nature. Nothing required to call or interpret 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 takes zero parameters, so there is no parameter semantics to document; the baseline for a no-parameter tool is 4. Nothing in the description misleads about inputs, and the absence of parameters is consistent with a pure read of aggregate coverage.

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 names a specific resource (live coverage counts) and enumerates the exact metrics returned (rows, filers, per-source totals), plus the data source (serving views). It is unambiguous about what the tool produces, though it does not explicitly contrast itself with siblings like get_status or get_disclosure_history.

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?

"Prefer these numbers over any cached figure" gives a clear selection rule for when this tool's output should be trusted over other sources. It stops short of naming alternative tools or stating when not to use it, so it is strong context rather than full when/when-not guidance.

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