Quattr

conversions_overview

Read-only

How many conversions / purchases / sign-ups did we get, and by which goal? Returns the OVERALL conversion count plus a per-goal breakdown — each goal labelled with YOUR OWN goal name (e.g. Purchase, Add to Cart, Registration), not a generic number — from your web-analytics source (GA4 / Adobe), optionally compared to a prior period. Pass goal to select one tenant goal by name or goalN id. A named goal's value is its conversion count (total_goalN); it is NOT the separate sitewide metrics: value metric. Defaults to QWA's All traffic sources scope; pass medium to request organic, paid, or another specific source. Exact google/cpc mirrors QWA PER METRIC: the overall Google Ads conversion count comes from paid stats, while metrics:['conversion_rate'] reads QWA's page_user_conversion rate under google/cpc + web. NEVER calculate conversion rate as paid conversions divided by paid clicks. The paid route has no GA goal breakdown; other requested GA-only extra metrics are omitted with an explicit note. Use for "Google Ads conversion rate", "paid conversion rate", "how many conversions / sign-ups / purchases", "conversions by goal", "goal completions", "transactions and revenue". For a side-by-side paid-versus-organic performance comparison use paid_organic_performance_comparison. NOT GSC clicks/impressions (use search_performance), NOT market share, NOT ad cost / CPC (use paid_search_overview).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "date_range": "<date_range>"
    },
    "name": "conversions_overview"
  }
}

Input Schema

Name	Required	Description
`goal`	No	Optional exact tenant goal name (for example "Purchase" or "Add to Cart") or goalN id. Selects that goal's conversion count; it does not turn the separate sitewide Total Value metric into a goal-specific monetary value.
`top_n`	No	How many goals to return (default all, capped at 10).
`medium`	No	Optional source-medium scope. Omit it (or pass "allsources" / "all traffic sources") to match QWA's All traffic sources conversion cards. Pass "google/organic" for organic-only, "google/cpc" for paid-only, or another exact medium.
`metrics`	No	OPTIONAL extra metrics to return alongside conversions + goals: "transactions" (purchase count), "revenue" (transaction revenue), "events" (total events), "value" (sitewide total value, not a named goal value), "conversion_rate" (the source-provided conversion-rate metric, never conversions/clicks). On exact google/cpc, conversion_rate follows QWA to page_user_conversion while the conversion count stays on paid stats; the other extras are unavailable and explicitly omitted.
`segment`	No	Tracked segment ID. On web-analytics scopes, omit it to get the list of available segments; pass "default" for the whole domain. Exact google/cpc is whole-domain only and defaults an omitted segment to "default".
`date_range`	Yes	Explicit date range, e.g. "2026-05-01 to 2026-05-31". Both endpoints are INCLUSIVE — the END day is covered (a 7-day range = 7 days). Quattr weeks run Sunday–Saturday; for "last week" use the most recent complete Sun–Sat span.
`granularity`	No	Return a whole-domain TIME SERIES bucketed by day / week / month / quarter instead of a single total — e.g. "weekly conversions over the last 13 weeks". Each bucket carries the overall count + per-goal counts keyed by YOUR OWN goal names (goalLabels maps the internal goalN ids to those names — always present goals by name, never by goalN). Mutually exclusive with comparison_range.
`date_range_mode`	No	REQUIRED when granularity is set. Use "calendar" for YTD or another explicit calendar period: keep the requested start and return only complete buckets inside it. Use "rolling" for "last N days/weeks/months/quarters": preserve N complete buckets by shifting the full window backward when needed.
`comparison_range`	No	Explicit comparison range for period-over-period, e.g. "2026-04-01 to 2026-04-30"

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds substantial behavioral context beyond that: goal names are rendered as the tenant's own labels, the google/cpc route has no GA goal breakdown and omits GA-only extras with an explicit note, and conversion_rate follows a different source path than the paid conversion count. This is real added value, though a 3 reflects that the annotations already carry the core safety/read-only disclosure.

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 answer to the core question is front-loaded and the routing/exclusion sentences are tight and useful. It is dense and long, with several parenthetical caveats that could be trimmed, but each sentence carries operational guidance rather than filler.

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?

For a complex 9-parameter tool with no output schema, the description covers edge cases an agent would otherwise guess at: the paid route's missing goal breakdown, omitted GA-only extras, the google/cpc per-metric mirroring, and default scoping. Nothing needed to call it correctly appears to be 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 the schema already documents all nine parameters thoroughly. The description reinforces a few semantics (goal selects a named-goal count, not the sitewide value metric; medium defaults to All traffic sources; conversion_rate must not be computed as paid conversions divided by paid clicks), but most of this is already present in the schema descriptions, so the incremental value is modest.

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 (returns overall conversion count plus a per-goal breakdown) and frames it as answering the 'how many conversions / sign-ups / purchases' question. It explicitly distinguishes itself from siblings by naming paid_organic_performance_comparison, search_performance, and paid_search_overview as the tools for adjacent jobs.

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

Usage Guidelines5/5

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

Gives explicit when-to-use phrasing ('Use for "Google Ads conversion rate"... "conversions by goal"...') and explicit when-not-to-use routing ('NOT GSC clicks/impressions (use search_performance), NOT market share, NOT ad cost / CPC (use paid_search_overview)'). The alternative tool for paid-vs-organic comparison is named with its condition.

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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