SEO Drift Monitor (April 2026)

SkillMonitoring & ops

SEO drift monitoring: capture baselines of SEO-critical elements, detect changes, and track regressions over time. Git for SEO — baseline, diff, and track changes to your on-page SEO. Use when user says "SEO drift", "baseline", "track changes", "did anything break", "SEO regression", "compare SEO", "before and after", "monitor SEO changes", or "deployment check".

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the SEO Drift Monitor (April 2026) skill

What this skill tells your AI

The instructions your AI receives, as published by agricidaniel/codex-seo in skills/seo-drift/SKILL.md and read by ahel’s review.

Shared Data Cache

Step 0 -- Check shared data cache:

Before gathering, check .seo-cache/ for reusable context from related SEO skills. Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.

Check these cache files when present:

  • .seo-cache/site-meta.json for domain, business type, industry, and crawl context

  • .seo-cache/audit-scores.json for prior full-audit priorities

  • .seo-cache/pages/{url-slug}/page-analysis.json for page-level context when a URL is provided

  • If found: parse and use clearly valid fields (note "Using cached [X] from [date]")

  • If missing, corrupt, or irrelevant: continue with fresh evidence

  • If the user says "refresh" or "re-run": ignore cache reads and overwrite on write

Git for your SEO. Capture baselines, detect regressions, track changes over time.


Commands

CommandPurpose
/seo drift baseline <url>Capture current SEO state as a "known good" snapshot
/seo drift compare <url>Compare current page state to stored baseline
/seo drift history <url>Show change history and past comparisons

What It Captures

Every baseline records these SEO-critical elements:

ElementFieldSource
Title tagtitleparse_html.py
Meta descriptionmeta_descriptionparse_html.py
Canonical URLcanonicalparse_html.py
Robots directivesmeta_robotsparse_html.py
H1 headingsh1 (array)parse_html.py
H2 headingsh2 (array)parse_html.py
H3 headingsh3 (array)parse_html.py
JSON-LD schemaschema (array)parse_html.py
Open Graph tagsopen_graph (dict)parse_html.py
Core Web Vitalscwv (dict)pagespeed_check.py
HTTP status codestatus_codefetch_page.py
HTML content hashhtml_hash (SHA-256)Computed
Schema content hashschema_hash (SHA-256)Computed

How Comparison Works

The comparison engine applies 17 rules across 3 severity levels. Load references/comparison-rules.md for the full rule set with thresholds, recommended actions, and cross-skill references.

Severity Levels

LevelMeaningResponse Time
CRITICALSEO-breaking change, likely traffic lossImmediate
WARNINGPotential impact, needs investigationWithin 1 week
INFOAwareness only, may be intentionalReview at convenience

Storage

All data is stored locally in SQLite:

~/.cache/codex-seo/drift/baselines.db

Tables

  • baselines: Captured snapshots with all SEO elements
  • comparisons: Diff results with triggered rules and severities

URL normalization ensures consistent matching: lowercase scheme/host, strip default ports (80/443), sort query parameters, remove UTM parameters, strip trailing slashes.


Command: baseline

Captures the current state of a page and stores it.

Steps:

  1. Validate URL (SSRF protection via google_auth.validate_url())
  2. Fetch page via scripts/fetch_page.py
  3. Parse HTML via scripts/parse_html.py
  4. Optionally fetch CWV via scripts/pagespeed_check.py (use --skip-cwv to skip)
  5. Hash HTML body and schema content (SHA-256)
  6. Store snapshot in SQLite

Execution:

python scripts/drift_baseline.py <url>
python scripts/drift_baseline.py <url> --skip-cwv

Output: JSON with baseline ID, timestamp, URL, and summary of captured elements.


Command: compare

Fetches the current page state and diffs it against the most recent baseline.

Steps:

  1. Validate URL
  2. Load most recent baseline from SQLite (or specific --baseline-id)
  3. Fetch and parse current page state
  4. Run all 17 comparison rules
  5. Classify findings by severity
  6. Store comparison result
  7. Output JSON diff report

Execution:

python scripts/drift_compare.py <url>
python scripts/drift_compare.py <url> --baseline-id 5
python scripts/drift_compare.py <url> --skip-cwv

Output: JSON with all triggered rules, old/new values, severity, and actions.

After comparison, offer to generate an HTML report:

python scripts/drift_report.py <comparison_json_file> --output drift-report.html

Command: history

Shows all baselines and comparisons for a URL.

Execution:

python scripts/drift_history.py <url>
python scripts/drift_history.py <url> --limit 10

Output: JSON array of baselines (newest first) with timestamps and comparison summaries.


Cross-Skill Integration

When drift is detected, recommend the appropriate specialized skill:

FindingRecommendation
Schema removed or modifiedRun /seo schema <url> for full validation
CWV regressionRun /seo technical <url> for performance audit
Title or meta description changedRun /seo page <url> for content analysis
Canonical changed or removedRun /seo technical <url> for indexability check
Noindex addedRun /seo technical <url> for crawlability audit
H1/heading structure changedRun /seo content <url> for E-E-A-T review
OG tags removedRun /seo page <url> for social sharing analysis
Status code changed to errorRun /seo technical <url> for full diagnostics

Error Handling

ScenarioAction
URL unreachableReport error from fetch_page.py. Do not guess state. Suggest user verify URL.
No baseline exists for URLInform user and suggest running baseline first.
SSRF blocked (private IP)Report validate_url() rejection. Never bypass.
SQLite database missingAuto-create on first use. No error.
CWV fetch fails (no API key)Store null for CWV fields. Skip CWV rules during comparison.
Page returns 4xx/5xxStill capture as baseline (status code IS a tracked field).
Multiple baselines existUse most recent unless --baseline-id specified.

Security

  • All URL fetching goes through scripts/fetch_page.py which enforces SSRF protection (blocks private IPs, loopback, reserved ranges, GCP metadata endpoints)
  • No curl, no subprocess HTTP calls -- only the project's validated fetch pipeline
  • All SQLite queries use parameterized placeholders (?), never string interpolation
  • TLS always verified -- no verify=False anywhere in the pipeline

Typical Workflows

Pre/Post Deployment Check

/seo drift baseline https://example.com     # Before deploy
# ... deploy happens ...
/seo drift compare https://example.com      # After deploy

Ongoing Monitoring

/seo drift baseline https://example.com     # Initial capture
# ... weeks later ...
/seo drift compare https://example.com      # Check for drift
/seo drift history https://example.com      # Review all changes

Investigating a Traffic Drop

/seo drift compare https://example.com      # What changed?
/seo drift history https://example.com      # When did it change?

Write to shared data cache

After completing all work, write a concise JSON summary to .seo-cache/ when the workflow produced durable findings. Use the schemas and naming rules in ../seo/references/shared-data-cache.md; include at least cache_type, analyzed_at, source URL/domain, key findings, issues, recommendations, and tool limitations. Add .seo-cache/ to .gitignore if it is missing.

Signals

GitHub stars
701
Forks
95
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
seo-drift
Source
github.com/agricidaniel/codex-seo