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

Annotations already cover read-only/idempotent/open-world safety, and the description adds a crucial analytical caveat not in annotations: the categories overlap and must not be summed. It also discloses that figures come from a self-hosted snapshot with reporting-population coverage and provenance.

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?

Front-loads the purpose, then use cases, then caveats/exclusions in three tight sentences. Every clause (example queries, the no-summing warning, the negative scope) earns its place by aiding selection.

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 return-content burden and does so, naming counts, rates, reporting-population coverage, and provenance. Combined with full parameter coverage and safety annotations, an agent has everything needed to call and interpret it.

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%, so state, month, and response_format are fully documented in the schema. The description adds no format or syntax detail beyond what the schema already provides, so the baseline of 3 applies.

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?

States a specific verb and resource (returns all ten FBI summarized UCR offense categories for one state-month) and names its source (CDE aggregate snapshot). It also implicitly distinguishes itself from trend and national siblings by naming what it is not.

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?

Gives concrete example queries ('FBI crime snapshot for Ohio in June 2022') and explicit exclusions (not a jurisdiction score, person-level search, or incident feed), and points to trend queries as the follow-on. It is slightly ambiguous about the sibling fbi_cde_state_reporting_coverage, since it claims coverage inspection as its own use case without naming that tool.

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