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

Annotations already cover read-only/idempotent/non-destructive safety, and the description adds real context beyond them: the cluster index vintage (2021), the pairing scheme (1–2 … 9–10), what each row measures (share of valid votes), and the unit-of-analysis warning. It does not describe ordering or how blocs are keyed, but for a no-param aggregate read this is substantive.

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?

Two dense sentences, front-loaded with what is returned, followed by the interpretive caveat. Every clause carries information; nothing is 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?

With no output schema and no parameters, the description must convey the return content, and it does (bloc → share of valid votes). The main omission is the election/timeframe being aggregated, which an agent would want before trusting the numbers; ordering and bloc labels are also unstated.

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?

Zero parameters, so there is nothing for the description to disambiguate; baseline applies. The description usefully fixes the grouping semantics (paired deciles 1–2 through 9–10, index 2021), which the empty schema obviously cannot convey.

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 verb+resource: the vote of Israel's municipalities grouped by CBS socio-economic cluster, with each bloc's share of valid votes. It implicitly separates itself from raw-result siblings (get_results) by the grouping and the 'describes places, not voters' framing, but never names an alternative explicitly.

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 clause and no sibling is named, so the agent must infer that this is the analytical/aggregate view versus get_results or check_coalition. The closing caveat 'Describes places, not voters' does imply a constraint on interpretation (don't read it as voter-level data), which is more than nothing.

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