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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description only needs to add behavior beyond those. It does: it names the three keyless sources, explains exact recruiting counts vs. national totals, describes the heuristic condition-to-specialty mapping with an explicit override, notes graceful Census-key degradation, and states that source failures are non-fatal. This is strong behavioral disclosure with no contradiction.

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 first clause front-loads the core purpose, and the rest is information-dense rather than padded: sources, outputs, failure behavior, and caveats all earn their place. The source enumeration is slightly run-on, but there is no wasted content.

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 and a complex three-source data aggregation, the description still explains what the agent will receive, including a readable brief with HIGH/MODERATE/LOW/NONE trial-activity banding and specialist availability. It also covers source-failure handling, the Census key prerequisite, and the informational-not-medical-advice boundary, making it complete enough to invoke correctly.

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 coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: condition is heuristically mapped to a provider specialty, specialty overrides that mapping, city/state scope the trial and provider search, and the Census component is optional and needs a key. This helps an agent choose and combine parameters correctly.

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 states a specific composite verb+resource: a one-call read of clinical-trial activity plus local specialist availability for a medical condition in a US geography. It clearly identifies the audience and decision context, and it is distinguishable from siblings like trials_search, npi_search_provider, and census_population because it is explicitly a combined site-feasibility synthesis.

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 gives a clear and concrete usage context: trial sponsors, CROs, or site-feasibility analysts deciding where to run a study. It does not explicitly name excluded cases or alternatives such as 'use trials_search for raw trial data,' but the intended situation is strongly implied and unambiguous.

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