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Election Index

When is the result final?

when_final
Read-only

When will a race's final (certified) result exist? Returns the expected window, its confidence (announced / precedent / estimate) and basis. Use this before asking or settling any "final result" question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
raceNoRace id, e.g. "president"; optional when the election has one race
electionYesElection id, e.g. "brazil-general-2026"; list ids with upcoming_elections

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaYesWhat this answer was built from; cite dataset_version
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds meaningful context beyond that: the tool returns a predicted window plus confidence tiers (announced / precedent / estimate) and basis, signaling this is an estimate-bearing forecast rather than a factual lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core question and followed by return shape and usage directive. No filler; every sentence carries distinct information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return-value detail need not be in the description, and the parameters are fully documented. The description covers purpose, output nature, and usage, leaving only minor gaps such as how the confidence tier should influence downstream behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (race, election, with its example and the pointer to upcoming_elections) are fully documented in the schema itself. The description adds no parameter-level detail, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific capability: forecasting when a race's certified final result will exist, distinct from any sibling tool (which report status, health, or sources rather than timing). The parenthetical '(certified)' clarifies the scope of 'final', removing ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit usage directive: 'Use this before asking or settling any "final result" question.' This tells the agent when to invoke it, but no alternative tool is named or excluded, so it stops short of full when/when-not routing.

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

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