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

Annotations already cover read-only, idempotent, and non-destructive properties, and the description adds substantial context beyond them: the aggregation-level logic, MEDSL/FEC coverage windows (President/Senate 1976-2024; House 2020+2022), OpenElections fallback, and per-district output for House. It omits any mention of pagination or rate limits, but the data-provenance detail is genuinely useful.

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?

Three dense sentences, well front-loaded with the core purpose before the coverage/aggregation nuance. Fairly long, but each clause carries distinct information (datasets, time windows, district behavior), so little is wasted.

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?

With no output schema, the description carries the burden of describing return values and does so explicitly (totals, shares, winner, margin, per-district for House). Combined with 100% parameter coverage and clear data-provenance notes, an agent has enough to call it correctly, though edge cases (missing data, ties) are not addressed.

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 baseline is 3, but the description adds meaning about the 'office' parameter by explaining that House returns one summary per district and that data sources vary by office. That is real semantic value beyond the schema field descriptions.

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 resource and enumerates the exact fields returned (total votes, vote share, winner, winning margin) scoped to one state/year/office. The description of aggregation behavior distinguishes it from raw-row siblings like election_results without naming them.

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?

Provides a concrete usage example ('who won the 2024 PA Senate race and by how much') and an explicit alternative to avoid ('rather than reading every county row yourself'). It does not name sibling tools such as election_results or list_elections, so the routing is implicit rather than explicit.

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