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

Beyond the read-only annotations, the description discloses that results come from a materialised snapshot, that computed_at indicates its age, and that low pct_with_votes often reflects legislative behavior rather than missing data. These are important behavioral and interpretive details that help the agent use the tool correctly.

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 front-loaded with the core definition and then adds usage guidance, interpretation caveats, and freshness information. Every sentence contributes useful context, and there is no redundant 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 one-parameter, read-only coverage tool with no output schema, the description gives enough detail about what the snapshot contains, how to interpret its ratios, and how fresh it is. Nothing essential for correct invocation appears to be 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 only parameter, max_items, is fully documented in the schema, including its default and maximum. The description does not add any parameter-specific meaning beyond that, so the high schema coverage sets the baseline at 3.

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 states that this tool returns a per-state depth snapshot of data completeness, including bill counts, vote/text/sponsor coverage, and session status. It is specific about the resource and metrics, but it does not explicitly name or distinguish itself from sibling tools such as list_states or list_statute_coverage.

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?

It gives a clear use case: check it before drawing conclusions from a thin result set, specifically to distinguish 'no such bills' from 'this state is thinly covered.' It also explains how to interpret the ratios. It does not explicitly name alternatives or state when not to use it.

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