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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds what the payload actually contains (weighted average, error margin, trend, 6-month evolution), which is valuable since no output schema exists, though it omits data freshness, update cadence and weighting methodology.

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 names the resource before the payload details. The bilingual parenthetical translation is slightly noisy but functional and adds clarity for non-French agents.

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 zero-parameter aggregate with no output schema, the description is nearly complete: it conveys the domain, the computation and the returned fields. Remaining gaps are freshness and how the weighted average is derived.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; the description correctly implies the call needs no arguments.

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 computation: the first-round ranking of the French 2027 presidential election, with the weighted average of recent polls, margin of error, per-candidate trend and 6-month evolution. 'Premier tour' implicitly separates it from get_runoff_polls, but no sibling is named 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?

Usage is only implied: an agent can infer this is the aggregate view for the first round, distinct from raw polls. There is no explicit when-to-use guidance or named alternative (e.g. get_trend, list_recent_polls) to route between tools.

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