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

With no output schema, the description carries the return burden and does so well: it discloses that results are bounded, paginated aggregate groups containing LIC/non-LIC and county counts plus source evidence. It also adds two genuine behavioral constraints beyond the readOnly/idempotent annotations - the counts' interpretive limits and the exclusion of 2026-2027 eligible/nominated tracts.

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 purpose is front-loaded as a question, followed by returns, filters, then usage caveats - a logical ordering with little filler. It is dense across four clauses, but each sentence contributes distinct information rather than restating the name.

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 6-parameter read-only aggregation tool with no output schema, the description supplies what's missing: the shape of the returned groups, the pagination behavior, the temporal scope, and the interpretation caveat. An agent has enough to invoke it correctly and interpret the result.

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 meaning of limit, offset, group_by, tract_type, jurisdiction, and response_format is already documented. The description restates the filterable dimensions ('narrow to one jurisdiction or tract type') but adds no syntax or format detail beyond the schema, 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?

The description names a specific verb (summarize) and resource (final 2018-cycle QOZ designations) and enumerates the exact aggregation dimensions (overall, jurisdiction, county, tract type, ACS data source). It clearly distinguishes this from the sibling search/lookup/compare tools, which return individual records or comparisons rather than aggregate distribution groups.

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?

It states the intended use ('coverage and market-screening summaries') and gives an explicit exclusion ('counts do not measure investment attractiveness', excludes 2026-2027 redesignation tracts). It does not, however, explicitly route to the alternative siblings (e.g., search_designations for individual tracts), so it stops short of full when-to-use/alternative guidance.

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