Seo ops
Agentic Framework for Modern Development
npx -y skills add LazyIsEfficient/agentic-os --skill seo-opsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
AI-powered SEO operations: keyword intelligence, competitor gap analysis, Google Search Console optimization, and trend detection. Use when asked to research keywords, analyze competitor content gaps, audit GSC performance, or detect trending topics. For growth experiments see growth-engine; for content optimization see autoresearch.
SKILL.md
2.5 KB, 287 tokens by cl100k_base, as published. Nobody here has run it
AI SEO Ops
AI-powered SEO operations: keyword intelligence, competitor gap analysis, GSC optimization, and trend detection.
Core Tools
| Tool | Purpose |
|---|---|
scripts/content_attack_brief.py | Full keyword intelligence pipeline: BOFU keywords, competitor gaps, decaying pages |
scripts/gsc_client.py | Google Search Console API client (CLI + library) |
scripts/gsc_auth.py | One-time OAuth setup for GSC access |
scripts/trend_scout.py | Multi-source trend detection across Google Trends, HN, Reddit, X |
Core Rules
- Run
scripts/gsc_auth.pyonce before any GSC tool — it saves the OAuth token locally. - Keywords are prioritized by Impact × Confidence (max 100) — focus on high-score BOFU targets first.
- Check the playbook in growth-engine before creating new content to apply proven patterns.
- Weekly cadence: full brief + daily striking-distance check + 2×/week trend scout.
References
- references/tool-reference.md — full CLI and library usage for all four tools
- references/configuration-and-scoring.md — environment variables, scoring model, funnel classification, workflow, dependencies