Quattr

paid_organic_overlap

Read-only

Which keywords are we paying for on Google Ads that we already rank for organically? Joins your paid query-set (paid clicks, cost, conversions per keyword) to your organic Search Console query-set (organic clicks, average position) on the keyword, and flags keywords where you BOTH pay AND already rank organic top-3 (possible wasted spend on owned terms). Use for 'are we paying for terms we already rank for', 'paid and organic keyword overlap', 'PPC cannibalization candidates'. Overlap is observational — it is NOT proof of cannibalization (that needs a controlled paid-pause test). Whole-domain.

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": "paid_organic_overlap"
  }
}

Input Schema

Name	Required	Description
`top_n`	No	How many overlapping keywords to return, ranked by paid cost descending.
`medium`	No	Organic source medium for the GSC read, default "google/organic". (The paid read is always Google Ads.)
`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.
`organic_rank_threshold`	No	Organic average-position threshold (1=top) at/above which an overlapping keyword is flagged as "already ranking" — default top-3.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint/openWorldHint=non-destructive, so this read-only read tool's safety profile is covered. The description goes further by explaining what is joined, that the paid read is always Google Ads while the organic medium is configurable, and that scope is whole-domain.

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-loaded with the core question, then mechanics, then caveat and scope. Every sentence carries information, though it is dense and slightly long with several stacked clauses.

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?

With no output schema, the description carries the return-value burden and does describe what is linked (paid clicks/cost/conversions, organic clicks/avg position) and what is flagged. Slightly short of a 5 since the exact output shape is only implied.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is already 3. The description adds genuine meaning: it clarifies the keyword-join basis, the top-3 flagging logic behind organic_rank_threshold, and the default organic medium, exceeding what the schema alone conveys.

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 operation (join paid Google Ads query-set to organic GSC query-set on keyword, flag top-3 overlap) and a clear scope (whole-domain). It is readily distinguishable from siblings like paid_organic_performance_comparison and total_search_share.

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 concrete trigger phrases ('are we paying for terms we already rank for', 'PPC cannibalization candidates') plus an explicit caveat that overlap is observational, not proof of cannibalization. It doesn't explicitly name alternative tools to use instead, keeping it just below 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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