Skill

Monitor SEO drift and catch ranking regressions before traffic drops

Baseline SEO metrics and compare snapshots to surface ranking drops, metadata overwrites, and directive changes after site changes.

Works with google search console

88
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out of 100
Updated today
Version 1.0.0

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Why it matters

Establish a known-good SEO baseline and automatically compare future snapshots to detect ranking drops, deindexation, overwritten metadata, directive changes, and missing schema that quietly erode organic traffic after migrations, redesigns, or deployments.

Outcomes

What it gets done

01

Capture search performance, indexation status, metadata, directives, and schema from Google Search Console and live page fetches

02

Diff current snapshots against prior baselines to surface ranking declines, lost queries, and disappeared indexed pages

03

Flag critical directive changes like new noindex tags, altered canonicals, or missing structured data

04

Rank findings by severity and preserve timestamped evidence for post-deployment verification

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-seo-drift | bash

Overview

SEO Drift Monitoring

SEO Drift Monitoring captures a known-good SEO baseline and compares later snapshots against it so regressions become visible. The skill combines search-performance data with live on-page checks to surface ranking drops, deindexation, overwritten metadata, directive changes, and missing schema before they quietly cost traffic. Use this skill when you need to baseline or monitor a site's SEO over time, check whether a migration, redesign, CMS change, or redeploy damaged SEO, compare current search performance and page metadata with a prior snapshot, investigate titles, descriptions, canonicals, robots directives, or schema that changed unexpectedly, or identify rankings or indexed pages that disappeared. For a one-time comprehensive SEO audit with no historical comparison, use a general SEO audit skill instead.

What it does

SEO Drift Monitoring captures a known-good SEO baseline and compares later snapshots against it so regressions become visible. The skill combines search-performance data with live on-page checks to surface ranking drops, deindexation, overwritten metadata, directive changes, and missing schema before they quietly cost traffic.

When to use - and when NOT to

Use this skill when you need to baseline or monitor a site's SEO over time, check whether a migration, redesign, CMS change, or redeploy damaged SEO, compare current search performance and page metadata with a prior snapshot, investigate titles, descriptions, canonicals, robots directives, or schema that changed unexpectedly, or identify rankings or indexed pages that disappeared.

When NOT to use: For a one-time comprehensive SEO audit with no historical comparison, use a general SEO audit skill instead.

Inputs and outputs

Inputs: The site property and key URLs in scope (prefer top organic landing pages, commercial pages, and URLs affected by recent releases), baseline or compare mode selection, snapshot storage location, and optionally a connected Google Search Console source for query, page, position, impression, click, and indexation signals.

Outputs: A dated snapshot containing search performance (clicks, impressions, CTR, average position), indexation status, metadata (title, meta description, H1), directives (canonical URL, robots header, meta-robots), structured data (schema types), and content shape (word count, content fingerprint). In compare mode, you receive a diff report grouped into five categories: rankings (queries that dropped or disappeared), indexation (pages that lost indexed status), metadata (titles, descriptions, H1s that changed or became blank), directives (canonicals that changed, newly introduced noindex), and schema (structured-data types that disappeared). Each change includes before/after values, comparison dates, severity level (Critical, Warning, Info), and likely cause labeled as an inference.

Integrations

Google Search Console for query and page clicks, impressions, click-through rate, average position, and indexed status or coverage evidence. Browser or web-fetch capability for current on-page values including metadata, directives, schema types, and content shape.

Who it's for

SEO managers and web developers who need to protect organic traffic during site changes. Technical SEO specialists monitoring post-migration health. Product teams validating that CMS updates or redesigns haven't introduced silent regressions. Anyone responsible for maintaining search visibility across deployments.

User: Baseline SEO for https://example.com before Friday's redesign. Track /, /pricing, and /docs.

Agent: I will capture a dated baseline for those three URLs, using Search Console for
query/page performance and live fetches for metadata, directives, schema, and content
shape. I will save it under the confirmed reports directory and use the same URL set and
Search Console window for the post-redesign comparison.

The skill ranks severity with directive and indexation failures first because they can suppress the entire page regardless of content quality. Critical issues include a page newly marked noindex, deindexed, or canonicalized to an unintended URL. Warnings cover material ranking declines, lost query visibility, blank or generic metadata, or missing schema. Info-level changes represent expected content or metadata updates with no observed search-performance harm. Search Console data can lag and may suppress low-volume queries; a live crawl cannot prove that Google has indexed a page or adopted its canonical. Position changes can reflect seasonality, SERP composition, location, device mix, or competitors rather than a site regression.

Source README

SEO Drift Monitoring

Overview

Capture a known-good SEO baseline and compare later snapshots against it so regressions become visible. The skill combines search-performance data with live on-page checks to surface ranking drops, deindexation, overwritten metadata, directive changes, and missing schema before they quietly cost traffic.

This portable version is adapted from the official seo-drift skill in NotFair.

When to Use

Use this skill when the user asks to:

  • baseline or monitor a site's SEO over time;
  • check whether a migration, redesign, CMS change, or redeploy damaged SEO;
  • compare current search performance and page metadata with a prior snapshot;
  • investigate titles, descriptions, canonicals, robots directives, or schema that changed unexpectedly;
  • identify rankings or indexed pages that disappeared.

For a one-time comprehensive SEO audit with no historical comparison, use a general SEO audit skill instead.

Prerequisites

Before capturing data:

  1. Confirm the site and the key URLs in scope. Prefer top organic landing pages, commercial pages, and any URLs affected by a recent release.
  2. Confirm baseline or compare mode. If no prior snapshot exists, use baseline mode and explain that there is nothing to compare yet.
  3. Ask where the snapshot should be stored. Use a local seo-drift/ directory alongside the user's other audit reports only after confirming the intended project or reports location.
  4. Prefer a connected Google Search Console source for query, page, position, impression, click, and indexation signals.
  5. Use a browser or web-fetch capability for current on-page values. Respect robots directives and avoid high-volume crawling.

If Search Console is unavailable, continue only with the on-page comparison and state that ranking and indexation drift could not be measured. Never infer missing Search Console values from a live crawl.

How It Works

1. Choose the comparison boundary

Record:

  • the site property and snapshot date supplied by the user or runtime;
  • whether the snapshot is a baseline or comparison;
  • the prior snapshot used for comparison, when applicable;
  • the exact URL set and search-data window;
  • any known migration, release, or CMS event that may explain expected changes.

Do not invent dates or silently compare mismatched date windows.

2. Capture the current snapshot

For the agreed URL set, collect:

  • Search performance: query and page clicks, impressions, click-through rate, and average position for a stable window;
  • Indexation: indexed status or coverage evidence for each key URL when the connected source exposes it;
  • Metadata: title, meta description, and H1;
  • Directives: canonical URL, robots header, and meta-robots value;
  • Structured data: schema types present;
  • Content shape: word count and another stable content fingerprint or summary useful for detecting large changes.

Persist both the values and their source. Keep unavailable fields as unknown; do not coerce them to zero or absent.

3. Diff against the previous baseline

Surface changes in five groups:

  1. Rankings: queries that dropped by the agreed threshold or disappeared from the observed window.
  2. Indexation: key pages that lost indexed status or a material drop in indexed-page count.
  3. Metadata: titles, descriptions, or H1s that changed, became blank, or fell back to a generic template.
  4. Directives: canonicals that changed or disappeared, and newly introduced noindex directives.
  5. Schema: structured-data types that disappeared from pages where they previously existed.

Separate expected content changes from unexplained regressions. A changed value is evidence of drift, not proof of causation.

4. Rank severity

Use these default levels:

  • Critical: an important page is newly noindex, deindexed, or canonicalized to an unintended URL.
  • Warning: a material ranking decline, lost query visibility, blank or generic metadata, or missing schema.
  • Info: an expected content or metadata change with no observed search-performance harm.

Put directive and indexation failures first because they can suppress the entire page regardless of content quality.

5. Report and preserve evidence

For every reported change, include:

  • URL and field or metric;
  • before and after values;
  • comparison dates and data window;
  • severity and likely cause, clearly labeled as an inference;
  • the next verification or repair action.

End by offering to create a new baseline only after the user confirms that intended changes and critical repairs are complete.

Example

User: Baseline SEO for https://example.com before Friday's redesign. Track /, /pricing, and /docs.

Agent: I will capture a dated baseline for those three URLs, using Search Console for
query/page performance and live fetches for metadata, directives, schema, and content
shape. I will save it under the confirmed reports directory and use the same URL set and
Search Console window for the post-redesign comparison.

Best Practices

  • Keep the key URL set stable so comparisons remain interpretable.
  • Compare equivalent Search Console windows and call out incomplete or delayed data.
  • Preserve raw snapshot evidence separately from the narrative report.
  • Treat missing data as unknown, not as a decline.
  • Verify a critical directive or canonical change with a second live fetch before escalating it.
  • Label likely causes as hypotheses until repository, CMS, deployment, or change-history evidence confirms them.

Limitations

  • Search Console data can lag and may suppress low-volume queries.
  • A live crawl cannot prove that Google has indexed a page or adopted its canonical.
  • Position changes can reflect seasonality, SERP composition, location, device mix, or competitors rather than a site regression.
  • The skill does not replace server-log analysis, full-crawl tooling, or manual review of a large migration.
  • Comparisons are unreliable when URL sets, date windows, locales, or device filters differ without normalization.

Security & Safety Notes

  • Write snapshots only inside the user-confirmed project or reports directory.
  • Do not store authentication tokens, cookies, or raw credentials in snapshots.
  • Use read-only Search Console access and non-mutating page fetches.
  • Avoid aggressive crawling; honor access restrictions and keep requests bounded to the agreed scope.
  • Do not change production metadata, canonicals, robots directives, or deployment settings without a separate, explicit implementation request.

Discussion

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