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

Beyond the read-only annotations, the description discloses data provenance (official state election-office and FEC content collected by Delilah), attribution posture, and critical interpretation rules for live_results, including per-contest entries and closed-primary party vote_pct semantics. These are exactly the behavioral details an agent needs to avoid misusing results data.

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 front-loaded with purpose, scope, and the GET endpoint, and every sentence carries useful information. It is somewhat dense, especially the long live_results sentence, but it is not padded or redundant.

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 read-only, open-world tool with no output schema, the description covers scope, provenance, key result semantics, and reporting constraints well. It does not fully describe the overall response structure beyond live_results, leaving some return-shape gaps.

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?

With 100% schema description coverage, the input schema already documents all seven optional parameters. The description adds no request-parameter guidance beyond what the schema provides, so the baseline 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 states a specific resource and scope: the 2026-11-03 election slate, with races, candidates, ballot measures per state, and official results. This is clear enough to identify the tool, but it does not explicitly route against sibling tools such as get_candidate, list_candidates, or get_ballot_measure.

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 gives explicit usage contexts ('who is running for X' and results questions) and important cautions about not comparing candidates across contests, not calling/projecting races, and reporting counts exactly. However, it does not say when to prefer a sibling tool over this one.

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