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

With no annotations, the description carries the full burden, and it delivers: it discloses that data comes from a 'materialised snapshot', that `computed_at` indicates its age, and that low pct_with_votes usually reflects legislative behavior rather than a data gap. This goes well beyond a bare 'get coverage' statement and helps the agent avoid misinterpreting results.

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 dense but every sentence earns its place: definition, use case, interpretation caveat, and data-freshness disclosure. It is front-loaded with the core purpose and does not repeat schema information.

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?

The tool is simple (one optional parameter, no output schema), and the description provides enough context to call it and interpret its results: what metrics are included, what the ratios mean, that it is a snapshot, and how to check its age. Nothing essential for correct usage 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?

Schema description coverage is 100% for the single optional `max_items` parameter, so the schema already fully documents it. The description does not add parameter-specific detail, but the baseline of 3 applies because the schema does the heavy lifting.

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 (per-state coverage) and a clear verb/function ('depth snapshot' showing how COMPLETE each jurisdiction's data is), and it enumerates concrete metrics: bill counts, share with votes/text/sponsor, and session status. This clearly distinguishes it from sibling tools like get_usage, get_session_breakdown, or list_states.

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 explicit guidance on when to use the tool: 'Use it before drawing conclusions from a thin result set, to tell no such bills apart from this state is thinly covered.' It also provides interpretive guidance (read ratios rather than raw percentages). It does not name alternative tools or state when not to use it, so it falls just short of a 5.

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