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

Annotations already flag this as read-only and non-destructive; the description adds meaningful behavioral detail: the exact output shape (percentile p25/p50/p75), the source (CMS HCRIS cost reports), a concrete example, and the per-call cost. It does not contradict the 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 front-loaded with purpose, then the return metric, then an illustrative example, then source and pricing. Every sentence adds value, and the example concretely demonstrates the tool's value without bloat.

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 no output schema, the description carries the full burden of explaining return semantics, which it does via the percentile metric and example. It also provides source and cost. Minor gaps remain around optional parameters and exact response structure, but for a simple lookup tool the description is largely complete.

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 0%, so the description must compensate. It names 'bed size' and 'state' as grouping dimensions and the example implies bed size is a numerical bed count, but it does not clarify that state is optional, accepted formats, or any constraints. This is partial compensation only.

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 a specific verb (benchmarking), a specific resource (hospital suppy chain efficiency against CMS peer cohort), and the exact metric returned (supply cost as % of operating expense at p25/p50/p75 by bed size and state). This makes it easily distinguishable from the many sibling benchmark tools.

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 opens with explicit use cases: benchmarking hospital supply chain efficiency against CMS peer cohorts or building a materials management cost reduction case. It does not name alternatives or exclusions, but it supplies clear context for when this tool is appropriate.

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