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Challenge a ruling

game_challenge

Challenges the last trivia ruling: three different AI models judge the player's answer against the clue, and the ruling flips only if at least two agree it should count. Once per clue. In a timeline game it re-checks the last placement against the years and says what was heard.

Input Schema

NameRequiredDescriptionDefault
slugYesThe game's slug
play_idYesThe play id from start_story

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With only terse annotations, the description carries real weight here and delivers: it explains the 2-of-3 majority mechanism, the per-clue rate limit, and that the tool reads back the ruling ('says what was heard'). That is exactly the kind of non-obvious behavior — a stateful, non-idempotent status change with a quota — that annotations alone (readOnlyHint=false, idempotentHint=false) cannot convey.

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 tightly packed sentences, front-loaded with the core action and effect, then the constraint, then the mode-specific variant. No sentence is filler — each one adds a rule or a behavior the agent could otherwise get wrong.

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?

For a two-parameter mutation with no output schema, the definition covers what the tool does, what changes, and the rate limit. Minor gaps remain: it doesn't say what happens if there is no prior ruling or the per-clue attempt is already spent (error vs. no-op), which matters for an operator with destructiveHint=false but a real state effect.

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 (slug, play_id) are already documented in the schema, including that play_id comes from start_story. The description adds no further parameter meaning, so the baseline 3 applies; the phrase 'the last ruling' implies how play_id is scoped but does not say it explicitly.

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?

The description names a specific verb ('challenges') and a specific resource ('the last trivia ruling'), and describes the outcome mechanic (three models judge, ruling flips on 2-of-3). It also distinguishes a second mode — timeline games re-check the last placement — so an agent can tell this apart from game_answer or check_accusation without opening the schema.

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?

The condition for use is clear (dispute the most recent ruling) and a hard constraint is stated explicitly ('Once per clue'), which prevents repeat-call mistakes. It stops short of naming the sibling an agent should call instead when the goal isn't to dispute a ruling (e.g. answering again via game_answer), so it does not reach a 5.

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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