An opinionated, GitHub-ready library of SEO automation scripts in Python and n8n, organized by job-to-be-done, with a decision rule, repo structure, and the maintenance tax most guides skip.
SEO reporting is high-frequency, low-value work: the ideal first thing to automate. Here is a no-code pull-transform-deliver pipeline and where it breaks.
How to check n8n workflow status: read execution state (Success, Error, Running), confirm a workflow is active, catch failures with Error Triggers, and get status alerts on your phone for self-hosted n8n.
Build a Python auditor that crawls redirects hop by hop to find loops, multi-hop chains, temporary redirects, and protocol hops that leak crawl budget and link equity.
A three-stage Python pipeline — regex rules, fuzzy slug matching, and content embeddings — that builds site-migration redirect maps automatically and routes only the genuinely ambiguous URLs to human review.
A working-code teardown of the three ways SEO teams collect Google SERPs at scale in 2026 – SerpAPI, Bright Data SERP API, and self-hosted Playwright – compared on cost, reliability, and maintenance.
A working Python pipeline that crawls your site, embeds every page, and ranks contextual internal-link suggestions by cosine similarity — with guardrails and an approval queue.
Search intent clustering is the practice of grouping the queries a site already ranks for by the intent behind them — what the searcher is actually trying to do — rather than by the words they happen to share. Do it well and every cluster maps cleanly to one page and one job; do it…
Find low-CTR pages, rewrite their titles and meta descriptions with an LLM under strict guardrails, ship the changes, and measure the CTR lift — a full Python pipeline.
Stop eyeballing the Search Console queries report. Build a Python pipeline that scores every GSC query by recoverable clicks and hands you a ranked SEO action queue.