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qrvote

Fix a quiz's answer key (allowed after people have answered; every score updates)

set_answer_key
Idempotent

Fix a quiz's answer key (allowed after people have answered; every score updates) Body: { answers: { : key | null } }. The key is an option index (single; yes/no uses 1 = yes, 0 = no), a list of option indexes (multi, all must match), or a list of accepted texts (short; case, accents and punctuation are ignored). null stops scoring that question. At least one question must stay scored. Needs the organizer key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe id in the public link, e.g. `scarecrow-contest-2026-ab12` from https://qrvote.org/c/scarecrow-contest-2026-ab12
answersYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations declare this is a non-readOnly, idempotent, non-destructive mutation; the description goes well beyond that by disclosing the downstream side effect (all scores recompute), the timing allowance (after people have answered), the auth need (organizer key), and a hard constraint on nulling questions. It does this without contradicting the hints.

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

Conciseness4/5

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

Front-loads purpose, then body format, then semantics and guards in a tight sequence with no filler. The only waste is restating the title verbatim in the first clause, which duplicates structured data.

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 no-output-schema mutation with a nested free-form parameter, the description covers format, side effects, guards, and auth. It stops short of saying whether an update merges with or replaces the existing key, and how invalid or unscored keys are reported back.

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

Parameters5/5

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

Schema coverage is only 50% and the answers object is a free-form map with no schema description at all, so the description carries the full burden — and does: answer-key format per question type (index, index list, accepted-text list), yes/no encoding (1=yes, 0=no), matching normalization (case/accents/punctuation ignored), and the meaning of null. That is everything an agent needs to construct the nested object.

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 verb and resource ('Fix a quiz's answer key') and immediately names the consequence ('every score updates'), so the agent knows this rewrites scoring configuration rather than responses or settings. This is clearly distinguishable from siblings like update_settings, add_entries, and add_judge.

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 a real usage precondition — 'allowed after people have answered' — which is exactly the fact an agent needs to know it can be called late in a campaign's life. It also states the guard ('At least one question must stay scored') and the auth requirement, but never names an alternative tool or an explicit when-not-to-use case.

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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