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

Annotations establish the safe read-only/idempotent profile, and the description adds substantial behavior beyond them: it discloses the returned fields (reporting population, full population, coverage percentage), an automatic warning threshold below 90 percent, pagination, and provenance. It also issues an interpretive boundary ('coverage is not data quality proof'), which is genuinely useful context.

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 the return contents, then usage examples, then the caveat. Dense and information-rich, though the sentence listing return fields is somewhat packed and could be split for readability.

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-value burden and does so by enumerating the payload fields and the warning behavior. It also covers scope, usage, and interpretive limits, leaving nothing an agent needs missing for correct invocation.

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 all six parameters including the state abbreviation constraint and YYYY-MM month formats are already documented. The description adds only mild value by characterizing the data as monthly observations subject to pagination, which maps loosely to limit/offset. Baseline 3 is appropriate.

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 precise verb (Inspect) and resource (monthly FBI UCR population coverage for one state) and explicitly scopes it to LiveDataLink's CDE aggregate snapshot. It also differentiates itself from the crime-trend siblings by framing its role as a check performed 'before interpreting its summarized crime trend.'

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?

Provides concrete usage triggers via examples ('was California's 2021 coverage complete?', 'find low-coverage months') and a clear context rule: use it to qualify an analysis before interpreting trends. It stops short of naming sibling tools like fbi_cde_state_crime_trend as explicit alternatives, so the routing is implied rather than stated.

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