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

With no annotations supplied, the description carries the full behavioral burden. It does disclose the shape and provenance of the response (issue positions, verbatim quotes, source URLs), which is genuinely useful, but it omits coverage caveats such as what happens when a race has no research, whether results are cached, or any access requirements. The qualifier 'researched race' hints at partial coverage without explaining it.

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?

A single front-loaded sentence that leads with the resource and follows with what each result contains; no filler or meta-commentary. The trailing enumeration of result fields is slightly long but each element (position, quote, source) is substantive.

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 one-parameter read tool with no output schema, explaining the return payload is the most important thing the description can do, and it does so. Remaining gaps (empty/partial coverage behavior, relation to sibling tools) are modest given the tool's simplicity.

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 coverage is 100% and the single parameter is fully documented in the schema, so the baseline is 3. The description does add one useful constraint by scoping it to a 'U.S. street address', implying non-U.S. addresses are out of scope, which is not stated in the schema.

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 the resource precisely: the set of researched races on the ballot for a U.S. street address, plus what each entry contains (issue positions, exact quote, source URL). An agent can immediately tell this is an address-to-ballot lookup. It stops short of differentiating itself from siblings list_issues and score_fit, which it never mentions.

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?

There is no explicit when-to-use or when-not-to-use guidance, and neither sibling (list_issues, score_fit) is referenced, even though an agent could plausibly confuse this with score_fit for evaluation tasks. Usage is only inferable from the required address parameter and the word 'ballot'.

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