cs:aeo

--- name: "cs-aeo" description: "/cs :aeo : Answer Engine Optimizationworkflow . Audit content for E-E-A-T and structural signals that drive LLM citations (ChatGPT, Perplexity,Claude ,Gemini , Mistral). Optimize content in 3 modes (conservative/balanced/aggressive). Track which LLMs cite which pages via a local ledger. Industry-aware thresholds (8 industries with YMYL calibration). Distinct fromSEO : refuses to optimize one at the expense of the other." --- #/cs :aeo : Answer Engine Optimization Command:/cs:aeo [action] [args] Thecs-aeo command is the entry point for AEOworkflows : audit → optimize → publish → track citations. ## Distinct From/cs:seo-audit These share a foundation (E-E-A-T) but optimize for different conversion events: - **/cs:seo-audit : optimizes for ranking and click-through in Google/Bing search results - /cs:aeo ** (this command) : optimizes for being cited as an authoritative source by LLMs They can be run on the same content. The cs-aeoagent will highlight this and recommend running both for high-leverage pages. ## When To Run - Auditing existing content for AI-search readiness (E-E-A-T + structural signals) - Optimizing a page for LLM citation before publishing - Tracking which LLMs cite which pages over time (citation ledger) - Researching whether AEO investment is worthwhile for a given piece of content - Benchmarking against competitors’ citation rates ## When NOT To Run - Pure click-through-SEO s without the intent to be cited by LLMs → use/cs:seo-audit - Content written in a brand’s voice with no factual claims (citations require facts) - Time-sensitive news (LLM training lag means citations may appear months later) - Topics where LLMs are already well-trained (e.g., elementary math) ## Actions ###audit : Assess content for AEO readiness ``bash /cs:aeo audit --input post.md --industry saas /cs:aeo audit --url https://example.com/blog/post --industry healthcare /cs:aeo audit --sample Returns composite 0-100 with per-dimension breakdown (E-E-A-T + Structure) and top 5 fixes in priority order. ### optimize : Generate AEO-improved variant bash /cs:aeo optimize --input post.md --mode balanced --output post-aeo.md /cs:aeo optimize --input post.md --mode aggressive --industry finance Three modes: - conservative : touch <10% of words (schema + corrections footer only) - balanced : touch <30% (citation markers + heading restructure + schema + footer) - aggressive : full restructure + fact-first lede + maximum citation density ### track : Log a citation you observed in an LLM response bash /cs:aeo track --url https://example.com/post --llm perplexity --query "what is AEO" --date 2026-05-17 Maintains a local ledger at ~/.aeo-data/citations.json. No telemetry. ### report : Aggregate citation report for a URL bash /cs:aeo report --url https://example.com/post Returns total citations, LLM coverage, velocity, top queries, verdict (EARLY / EMERGING / STRONG). ### export : Emit citation ledger as CSV bash /cs:aeo export --output citations.csv For reporting to clients / stakeholders. ## Minimal Intake (3 Questions) | Q | Asks | When | |---|---|---| | Q1 | What action : audit / optimize / track / report? | Always | | Q2 | Industry (saas / healthcare / finance / legal / ecommerce / b2b / media / education) | Always (calibrates thresholds) | | Q3 | For optimize: mode (conservative / balanced / aggressive)? | Only when action=optimize | Most invocations exit intake after Q2. ## Workflow ``bash # Phase 1: Audit python3 marketing-skill /skills /aeo/scripts/aeoaudit.py --input <file>--industry <industry> # → composite score 0-100 + top fixes # Phase 2: Optimize (if audit < industry threshold) python3 marketing-skill /skills /aeo/scripts/aeooptimizer.py \ --input <file>--mode <mode>--industry <industry>--output <file>-aeo.md # → optimized variant + changelog # Phase 3: Publish (manual step : review the optimized variant, then deploy) # Phase 4: Track (over 4:12 weeks) python3 marketing-skill /skills /aeo/scripts/citation_tracker.py \ --action add--url <url>--llm <llm>--query <query>--date <YYYY-MM-DD> # → ledger updated # Phase 5: Report (monthly) pytho