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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds real behavior beyond that: sign-in is required, results include measured freshness, completeness and caveats, and counts carry source-specific meanings. That is meaningful operational context an agent could not get from the annotations alone.

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?

Four short sentences with the core capability front-loaded and no filler. The telegraphic style ('complaints are separate from violations') is dense but each sentence carries a distinct fact.

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?

For a 7-parameter read-only listing tool with no output schema, the description covers what is returned (freshness, completeness, caveats), the auth requirement, and the main semantic pitfall (complaints vs violations). Little an agent needs in order to call it correctly 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%, so the schema already explains page/start, name filtering before pagination, and the pipeline_dataset scoping. The description adds only the dataset enumeration and a semantic caveat about counts, which is baseline-level value when 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?

States a specific verb ('List') and resource ('source and place coverage') and enumerates exactly the four datasets accepted by the enum (inspections, violations, pipeline, certificates). It does not explicitly distinguish itself from the sibling get_coverage, so it falls short of a 5.

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?

Offers useful context — 'Requires sign-in' and 'Licensing has no coverage endpoint' effectively rules out one dataset — but never names an alternative tool or states when to prefer a sibling such as get_coverage. Guidance is implied through data semantics rather than tool selection.

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