SEO Skill

Check whether search changes overlap a confirmed Google update.

Use this when a property movement overlaps talk of a Google update. The report checks official dates and the observed anomaly window, then points to the segments and pages that need real investigation.

Run this report from the CLI, an MCP client, or application code. Every surface uses the same report definition and returns the same evidence. JSON is the source of truth; Markdown makes it readable without hiding dates, limits, warnings, or skipped work.

What this report helps you decide

Did this property’s unusual movement overlap a confirmed Google ranking update?

  • A traffic anomaly falls near dates listed on Google’s Search Status Dashboard.
  • You need timing context before a deeper winner and loser review.

Command facts

Report id
update-correlation
Execution
Local process
Outputs
JSON and Markdown
Example parameters
site, days, recentDays, paddingDays, refresh
Agent discovery
seo reports describe update-correlation --json
Interactive prompts
Human CLI commands only

When this report is not the right tool

These cases need a different report, more evidence, or a human decision. Do not force this report to answer a question its data cannot support.

  • You need winners, losers, page patterns, and known site changes around a confirmed update window. Recommended report: Review winners and losers around a Google update. Run the update postmortem. It anchors matched Search Console comparisons to the official window, inspects segment and page patterns, and keeps migrations, releases, tracking changes, and other confounders visible.
  • You need proof that a Google update caused a traffic change. No automated report can prove that from timing overlap. Compare affected and unaffected segments, representative pages, known site changes, demand, seasonality, and later recovery evidence. Update correlation only establishes whether the dates overlap.

Data sources and inputs

  • Search Console traffic anomaly result. Provides the observed movement, baseline, recent window, and significance evidence.
  • Official Google ranking update windows. Provides confirmed rollout dates from Google Search Status.

What this report checks

  • Matches the observed anomaly window against confirmed ranking update dates with an explicit padding period.
  • Classifies the timing overlap while keeping unrelated releases, demand changes, and other confounders unresolved.

How it works

  • Overlays the observed anomaly window with confirmed update dates and an explicit padding window.

The JSON result keeps dates, thresholds, limits, skipped work, and source completeness beside the finding. Missing, partial, capped, filtered, and complete data remain different states.

Run the report from the CLI

Compare traffic movement with confirmed Google update windows. Agents and CI should inspect the live schema before their first run.

Run it from the CLI

seo update-correlate --project example

Check the agent input schema

seo reports describe update-correlation --json

Run it from an agent or script

seo reports run update-correlation --params '{"site":"sc-domain:example.com","days":90,"recentDays":7,"paddingDays":2,"refresh":false}' --json

Project profiles can fill supported property and analytics inputs for the human-facing commands. The catalog form shown here is explicit by design, so agents and CI jobs do not prompt or guess.

How an MCP agent should use it

Call seo_describe_report first so the agent sees when this report is useful and gets the current input schema. Then callseo_run_report with the validated parameters. Read the status, warnings, source limits, and skipped sections before acting on a finding.

Describe the report with MCP

{
  "id": "update-correlation"
}

Run the report with MCP

{
  "id": "update-correlation",
  "params": {
    "site": "sc-domain:example.com",
    "days": 90,
    "recentDays": 7,
    "paddingDays": 2,
    "refresh": false
  }
}

Use a follow-up report returned by the result instead of guessing the next tool. The local MCP server and CLI use the same report definition and evidence. Their outer transport envelopes differ.

Use the report in a TypeScript app

Install seo as a project dependency, then call the same report catalog used by the CLI and MCP. executeReportrejects an unknown report id or invalid parameters. Provider and runtime failures come back as structured results withisError set.

Install the library

npm install seo

Run this report from TypeScript

import { executeReport } from 'seo/mcp'

const result = await executeReport(
  'update-correlation',
  {
  "site": "sc-domain:example.com",
  "days": 90,
  "recentDays": 7,
  "paddingDays": 2,
  "refresh": false
},
)

console.log(result)

The TypeScript library guide also covers direct core functions, schema discovery, and the difference betweenexecuteReport and runReport.

What comes back and how to read it

  • A timing classification with the anomaly dates, matching official updates, padding, and source status.
  • Caveats and next investigations for segments, templates, and representative pages, with no causal verdict.
  • Overlap is a reason to inspect affected segments and page types. It is not a diagnosis by itself.

Start with dataStatus, source details, warnings, and caveats. Then inspect the observed evidence before derived findings or suggested actions.

What this report cannot tell you

  • Sites change while updates roll out, and unrelated demand or technical events can share the same dates.

What to do next

  1. Use the update postmortem workflow to inspect winners, losers, and known confounders.
  2. Audit representative pages before making template-wide changes.

Sources behind the guidance

These primary sources define the provider data or search controls used in the interpretation above.

Browse all reports in Property diagnosis.