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rooquiz

RooQuiz

get_form_stats

Read-only

Retrieve submission statistics for any quiz form over a selected period, including scores, trends, channels, devices, and per-question answers. Use it to identify performance gaps and improve quiz results.

Instructions

Read submission statistics for a form in the current team over the last N days: KPI overview (total / today / last 7 / last 30, unique examinees, anonymous, report status counts, average score, latest submission), daily submission trend, channels (by utm_source), UTM combos, login types (anonymous vs registered), device breakdown, and per-question answer distributions. Use this to gauge how a quiz is performing and to suggest improvements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook-back window in days, default 30, max 180
formIdYesThe form UUID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLook-back window actually used
trendNoOne entry per day in the window, zero-filled
formIdNoThe form these stats belong to
devicesNoSubmissions by device type
channelsNoSubmissions by utm_source
overviewNoKPI block: { totalSubmissions, todaySubmissions, yesterdaySubmissions, last7daysSubmissions, last30daysSubmissions, uniqueExaminees, anonymousSubmissions, reportCompleted, reportFailed, reportPending, avgScore, latestSubmittedAt }
utmCombosNoSubmissions by UTM combo
loginTypesNoAnonymous vs registered submissions
answerDistributionsNoPer-question answer distribution (choice-style questions only)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description starts with 'Read', which is consistent. It adds meaningful behavioral context by specifying team scoping, the time window, and the full breadth of returned statistics, giving the agent a good sense of what an invocation will produce. It does not cover performance or rate limits, but the annotations and output schema lower the burden.

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?

The description is dense but every element earns its place: the opening verb/resource/scope, the detailed list of returned statistics, and the closing use case. It is front-loaded with the core action and uses an em-dash list to keep the information structured and scannable.

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

Completeness5/5

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

Given the tool's moderate complexity, the 100% schema coverage, the presence of an output schema, and annotations covering safety, the description is complete. It explains what the tool does, what data it operates on, the team scope, the time-window parameter, and the intended usage. Nothing essential is missing for an agent to call it correctly.

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 coverage is 100%: formId and days both have descriptions in the input schema. The description reinforces the meaning of days ('last N days') and adds the 'current team' scope, but it does not add parameter-level detail beyond the schema, so the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Read submission statistics for a form in the current team over the last N days.' It then enumerates the exact categories of statistics returned, making it easy to distinguish from the form CRUD siblings and from get_form_funnel even 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 description gives an explicit intended use: 'Use this to gauge how a quiz is performing and to suggest improvements.' It does not mention alternatives or exclusions, but the clear use case and the read-only scoping in the first sentence provide enough context for an agent to select it appropriately.

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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