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rooquiz

RooQuiz

get_form_funnel

Read-only

Analyze a form's conversion funnel over a chosen period to identify where respondents drop off. Track stage, channel, and UTM performance to pinpoint stalls and improve conversion.

Instructions

Read the conversion funnel for a form in the current team over the last N days, from the form_sessions telemetry: overall stages (viewed → started → submitted → leadCaptured → reportViewed → ctaClicked → shared), per-channel funnel (by utm_source, with embedded flag), UTM combos, and drop-off points (which question unsubmitted sessions stalled on). Use this to find where respondents drop and improve conversion.

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
formIdNoThe form this funnel belongs to
dropOffNoWhere unsubmitted sessions gave up
overallNoStage counts: { viewed, started, submitted, leadCaptured, reportViewed, ctaClicked, shared }
channelsNoFunnel split by channel
utmCombosNoFunnel split by UTM combo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful context beyond that: the scope ('in the current team'), the telemetry source ('form_sessions'), and the exact stage/breakdown details. No contradiction with annotations.

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?

The description is dense but not bloated. It front-loads the verb and resource, uses a colon to organize the breakdown list, and ends with a practical usage sentence. Every segment contributes information, though the enumeration is long.

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?

With an output schema present, the description only needs to convey scope, timing, and intended use, which it does thoroughly. It covers the team scope, the look-back window, the breakdown dimensions, and the drop-off analysis use case. Nothing needed for correct invocation is missing.

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 formId and days are already documented with defaults and bounds. The description only echoes 'form' and 'last N days' without adding new parameter semantics, so the baseline score 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 the conversion funnel for a form...' and enumerates the exact breakdowns available (overall stages, per-channel, UTM combos, drop-offs). This clearly differentiates it from sibling tools like get_form_stats or list_records.

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?

It states a clear use case: 'Use this to find where respondents drop and improve conversion.' It does not explicitly name alternatives or when-not-to-use scenarios, but the funnel-specific context makes the appropriate usage apparent.

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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