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

With no annotations, the description carries the full burden and does well: it discloses the rolling/resolution behavior, the two extra response fields (current_slug, rolls_to_next_at), the HTTP verb and path, and the $0.02 x402 cost. It does not state rate limits or error behavior, but the core behavioral profile is clearly conveyed.

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 purpose is front-loaded, but the recurring-question phrase 'Who controls the House after the next election?' is repeated verbatim in the first two sentences, wasting space. The bracketed endpoint/pricing/docs metadata at the end is useful but dense.

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?

Given zero parameters, no output schema, and no annotations, the description supplies what an agent needs: what the tool returns extras-wise and how the evergreen resolution works. Only the absence of any stated usage/alternative framing keeps it from being fully complete.

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 schema to document and no parameter ambiguity for the description to resolve; the baseline of 4 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 names a specific verb+resource ('Live probability: Who controls the House after the next election') and pinpoints the tool's distinguishing trait versus the many other probability_* siblings: it is the stable evergreen URL for a recurring question. An agent can tell it apart from probability_get or probability_board_politics-us without opening any schema.

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 implied rather than stated: 'Stable evergreen URL for a recurring question... auto-resolves to the current market instance and rolls forward on resolution' tells the agent this is for a recurring question rather than a specific market instance, but it never explicitly says when to prefer this over probability_get or a board endpoint, and offers no exclusions.

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