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

The description goes well beyond the annotations by disclosing that the tool queries no data, that verdicts come from a coverage registry, and that NOT_COVERED is measured rather than inferred from empty search. It also discloses limitations such as single-state geography and lack of calibrated probability. This is valuable behavior an agent could not infer from 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?

The description is dense but each sentence adds a distinct point: what it reports, when to call it, how to call it with no arguments, how to call it with filters, and why the result is trustworthy. It is slightly longer than strictly necessary but front-loads the key purpose and usage guidance.

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?

This tool has zero required parameters and no output schema, so the description carries a high burden. It fully covers what the tool returns (full grid vs. one-slice verdict), the set of possible verdicts, the source of truth, and limitations. Nothing an agent needs to correctly invoke and interpret the tool 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 already describes both parameters with 100% coverage, so the baseline is 3. The description adds meaning by explaining the no-argument mode, the state/event_type narrowing mode, and the output shape (COVERED, NOT_COVERED, or UNKNOWN) for those parameters. It also ties event_type to the same vocabulary as search_property_events, which helps the agent reuse known values consistently.

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 resource ('coverage registry') and what the tool does: reports measured coverage and known gaps. It distinguishes itself from event search by explicitly warning not to conclude an empty result means an absent market, and by referencing the same event_type vocabulary as search_property_events.

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 explicit when-to-use guidance: 'Call this before concluding that an empty result means an absent market.' It also tells the agent exactly how to invoke it differently depending on need: no arguments for the full grid, or state/event_type for a direct verdict.

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