Pinpoint where organic traffic changed and why
Create a tight "before vs after" diff for Google Search Console (queries, pages, CTR, position) to identify the specific segments driving traffic loss or gains. Produces a prioritized action list and hypotheses per segment.
Build a Search Console before/after impact diff. Output: - Top 10 loss segments with hypotheses (why each dropped) - Top 10 win segments (what to replicate) - Action plan: quick wins (this week) + strategic fixes (this month) - SERP change notes (AI overviews, feature shifts, ad density) Inputs: - Baseline dates: - Affected dates: - Export snippets or summaries: - Primary conversions impacted: - Any known SERP feature changes:
This recipe turns vague "SEO is down" into a segmented diagnosis you can act on.
Triage SEO volatility during confirmed ranking updates
When Google launches a core update, sites can see major swings in traffic and rankings. This recipe creates a "war room" checklist: define the baseline, segment impact, avoid premature changes, and produce a recovery roadmap once rollout stabilizes.
Turn a spreadsheet of SKUs into SEO-ready product pages
Feed it your product catalog — CSV, spreadsheet, or Shopify export — and get back unique, keyword-aware descriptions for every SKU. Useful when your current copy is thin, duplicated, or straight from the manufacturer.
Wikipedia-grade AI pattern removal
Comprehensive AI writing cleanup based on Wikipedia's WikiProject AI Cleanup guidelines. Catches 24+ distinct patterns including inflated symbolism, em dash overuse, rule of three, copula avoidance, and sycophantic tone.
Real sources, named experts, actual quotes
Deep research that finds primary sources with named individuals, community sentiment from Reddit/HN/X, and news coverage. No summaries of summaries — actual quotes with URLs.