SEO, AEO, and content distribution skills for Claude — a tested workflow for researching, writing, and distributing content that gets cited by AI answer engines and ranks in search.
Two skill groups:
- Research & Audit — understand what AI engines are citing, find keyword gaps, audit existing pages
- Content & Distribution — write AEO-optimized content, distribute it via Reddit/LinkedIn/etc, track citations
Designed to complement Ahrefs/Semrush by:
- Understanding your site's content, intent, and target audience
- Recommending UX and IA changes
- Reporting on how real people phrase questions in your niche (Reddit language glossary)
- Validating schema against your pages' content type
Research & Audit skills use a Coordinator → Haiku → Sonnet pipeline to balance speed, cost, and quality:
- Coordinator (main Claude): gathers input, orchestrates agents
- Haiku agents: parallel mechanical extraction — API calls, page crawls, data collection
- Sonnet agent: analysis, synthesis, and report writing
The output reports include a Token Usage Summary with per-agent input/output tokens and estimated cost. The orchestrator aggregates token costs across all three skills into a single grand total.
Each skill has a CONFIG.example.md. Change it to CONFIG.md in the same folder and fill in your values (site URL, tracker paths, etc.). CONFIG.md is gitignored — your project-specific values stay local.
Research & Audit
- Setup
- Quick Start
- 0. aeo-seo-strategy-orchestrator
- 1. aeo-topic-research
- 2. seo-keyword-research
- 3. aeo-seo-site-audit
Content & Distribution
- 4. growth-pm
- 5. aeo-content-writer
- 6. publish-checklist
- 7. distribute-social
- 8. distribute-outreach
- 9. reddit-content
- 10. linkedin-content
The aeo-seo-site-audit skill uses curl to analyze schema markup, but Claude Web doesn't have permission to run curl, so you'll be prompted to check schema manually using Google's Rich Results Test.
Additionally, running the audit skill locally allows your AI coding agent to run a continuous improvement loop (audit -> fix -> audit -> fix) without needing to deploy each fix.
- A paid Ahrefs account gives you access to real keyword data such as search volumes, difficulty scores, and competitor traffic, and AI engine visibility.
- Otherwise, skills use web-scraped estimates instead of actual data.
Use aeo-seo-strategy-orchestrator for a unified audit that runs all three core skills in parallel and synthesizes recommendations into one list.
Or, run each skill separately.
* aeo-topic-research → Recommends topics, content format, and UX changes for AEO
* seo-keyword-research → Find competitive keywords, content gaps, and IA recommendations for SEO
* aeo-seo-site-audit → Audit & optimize your pages for SEO and AEO
File: aeo-seo-strategy-orchestrator/SKILL.md
An all-in-one strategy. This orchestrates all three core skills (aeo-topic-research, seo-keyword-research, aeo-seo-site-audit) in parallel, then a Sonnet synthesis agent unifies all findings into a single ranked strategy.
- Coordinator: gathers input, launches three sub-skill agents simultaneously
- Sub-skill agents (parallel): each runs its own full Haiku + Sonnet pipeline
- Sonnet Synthesis Agent: merges all three reports, deduplicates, ranks recommendations, aggregates token costs
- Your domain (i.e. your homepage URL)
- [Optional] 2–5 competitor URLs
- [Optional] Target website URLs to audit (5–10 core pages)
- [Optional] Ahrefs account for real keyword data
- [Optional] Market/niche and business goals
- [Optional] Current site pain points or goals
- Topic research — what AI engines are answering, what's being cited
- Competitive analysis — keyword gaps, ranking opportunities, quick wins
- Site audit — technical SEO, content quality, current AEO level
- Functionality analysis — site architecture, feature gaps, UX friction points
- Unified strategy — integrated list of prioritized recommendations
A strategic report with:
- Executive summary with Top 3 Opportunities (colored priority badges)
- Unified prioritized recommendations: summary table (one row per item, colored badge) followed by detailed items; all 🔴 Critical and 🟡 Important issues always included; top 2 🟢 Enhancements per skill shown, with a note if more were omitted
- Detailed findings grouped by category (AEO research, keywords, on-page, functionality)
- Aggregated Token Usage Summary with grand total cost across all agents
File: aeo-topic-research/SKILL.md
Discovers what questions AI engines are answering in your niche, which domains and pages they're citing, and what content formats are winning citations — so you know exactly what topics to create for AEO visibility.
- Coordinator: gathers input, orchestrates two waves of Haiku agents
- Haiku Brand Radar Agents (parallel, one per AI engine): Steps 3–5 — Brand Radar API calls for AI questions, cited domains, cited pages
- Haiku Reddit Agent: Step 6 — web searches + thread fetches per topic cluster
- Haiku Page Crawl Agents (parallel, one per URL): Step 7 — extract content format and structure signals; sampling ensures at least 2 pages per content format type (guide, listicle, comparison, FAQ/definition, HowTo, stat roundup) for reliable pattern detection
- Sonnet Agent: Steps 8–11 — synthesize patterns, score opportunities, generate report
- Your brand name and website URL
- Your market/niche (e.g. "email marketing software")
- [Optional] 2–5 competitor brand names to compare against
- [Optional] Which AI engines to prioritize (ChatGPT, Perplexity, Google AI Overviews, Gemini)
- [Optional] Ahrefs account for real Brand Radar citation data
- AI-answered questions — what are people asking that AI search engines are answering?
- Reddit language — how real people phrase questions and describe problems in your niche, surfacing vocabulary and unmet needs that formal research misses
- Cited domains & pages — who is AI citing most often, and which specific pages win citations?
- Content patterns — what topics, formats, and structures get cited by AI engines?
- Content gaps — opportunities where you can create content that AI engines will cite
- Content presentation & UX — navigation aids (TOC, jump links, sticky nav), multimedia gaps, and formatting patterns from citation-winning pages
A prioritized content opportunity brief including: a summary table of all recommendations (one row per item, colored priority badge) followed by detailed items with content briefs; topic clusters ranked by citation potential; a Reddit language glossary; competitor citation analysis; winning content formats; content presentation recommendations; and a Token Usage Summary.
File: seo-keyword-research/SKILL.md
Analyzes competitor websites to reverse-engineer their SEO strategies, identifies content gaps and keyword opportunities, and produces a prioritized list of target keywords with ranking and traffic potential.
- Coordinator: gathers input, orchestrates two waves of Haiku agents
- Haiku Competitor Agents (parallel, one per competitor): Steps 3–4 — Ahrefs metrics + top keywords (Step 3), crawl key pages (Step 4); each competitor gets exactly 2 pages per type (homepage, blog/resource, category/topic hub, product/service detail) for consistent cross-run comparisons
- Haiku Keyword Research Agent: Step 5 — Ahrefs keyword explorer calls using seeds from competitor data
- Sonnet Agent: Steps 6–11 — content analysis, gap analysis, ranking evaluation, prioritization, IA recommendations, report
- Your domain (i.e. your homepage URL)
- [Optional] 2–5 competitor domains
- [Optional] Connect your Ahrefs account for real data
- Competitor content strategy — what topics do they cover, and how?
- Content gaps — keywords they rank for that you don't (and vice versa)
- Keyword opportunities — ranked by ranking potential, search volume, and competitive difficulty
- Traffic analysis — estimated traffic potential and ROI for target keywords
- Information architecture — navigation structure, topic cluster hub pages, internal linking, and content silos based on keyword clustering
When the Ahrefs MCP server is connected, you get real data:
- Exact search volumes and traffic figures
- Ahrefs keyword difficulty scores (0–100)
- Actual competitor organic traffic
- SERP feature data and adjustments
A competitive keyword strategy with: a summary table of all recommendations (one row per item, colored priority badge) followed by detailed items; keyword tiers (Quick Wins / Strategic / Long-term) with traffic estimates; content gap analysis; information architecture recommendations (navigation changes, hub pages, internal linking, content silos); and a Token Usage Summary.
File: aeo-seo-site-audit/SKILL.md
Analyzes your website pages for content quality, schema markup completeness, and AEO (Answer Engine Optimization) — with actionable recommendations for improving AI citation potential and search ranking for your existing pages. Complements an Ahrefs Site Audit by covering content depth and AI-readiness that Ahrefs cannot assess; relies on Ahrefs for technical SEO (title tags, meta descriptions, broken links, crawlability, etc.).
- Coordinator: gathers input, launches one Haiku agent per URL (+ one Ahrefs agent if project ID provided) in parallel
- Haiku URL Agents (parallel, one per URL): fetch raw HTML, extract JSON-LD schema, extract content and authority signals; after user-specified URLs, required representative sampling adds 1–2 pages per type not yet covered (static content, dynamic/app route, category/listing, utility) to prevent missing CSR rendering gaps
- Haiku Ahrefs Agent (if project ID provided): pulls technical audit findings from Ahrefs API
- Sonnet Agent: schema validation, content analysis, gap prioritization, report writing
- 1 or more target URLs from your website
- [Optional] Ahrefs Site Audit project ID — automatically pulls technical audit findings to combine with content analysis
- [Optional] Business context and content goals (e.g. targeting AI search engines)
- Schema markup — validates JSON-LD completeness and accuracy (FAQPage, HowTo, Article, Organization, etc.), flags missing or mismatched schema
- Content quality — depth, directness, E-E-A-T signals, readability, topical coherence
- AEO optimization — direct-answer formatting, author credentials, source citations, freshness signals, content structure for AI extraction
A prioritized audit report with: a summary table of all recommendations (one row per item, colored priority badge) followed by detailed items; findings grouped by severity (🔴 Critical / 🟡 Important / 🟢 Enhancement); specific schema fixes with effort estimates; a page-by-page breakdown; and a Token Usage Summary. If an Ahrefs project ID is provided, the report integrates Ahrefs technical findings alongside the content/AEO analysis.
File: growth-pm/SKILL.md
Central coordinator for the content pipeline. Maintains a prioritized task board across 4 workstreams (Research & Audit, Content Creation, Content Publication, Distribution), routes work to the right skill, tracks citation performance, and learns from GSC data and human feedback to improve future routing and flag skill updates.
- "What should we work on next?"
- "Run the daily growth routine"
- "Check the tracker and prioritize"
- "What's performing well?"
- "Check citations for [post slug]"
- Tracker file (path in
CONFIG.md) - [Optional] GSC data via Ahrefs MCP
- [Optional] Human feedback or experiment results
Ranked task board across 4 workstreams, performance signals, skill update flags, and an exact handoff prompt for the target skill.
File: aeo-content-writer/SKILL.md
Writes AEO-optimized blog posts using BLS, O*NET, or equivalent authoritative data. Output includes the post component, route file, blog index entry, thumbnail, and sitemap update — ready to ship.
Lead with finding → show evidence → explain meaning → caveats → actionable takeaway. Every post includes 4 FAQ pairs that drive FAQPage JSON-LD schema for AI citation signals.
- Post topic and target persona
- Data sources (BLS/O*NET or custom)
- Tone guide path (set in
CONFIG.md)
All files needed to publish: post component, route page, blog index entry, sitemap block.
File: publish-checklist/SKILL.md
Config: CONFIG.example.md → copy to CONFIG.md
Validates any page before it goes live — SEO metadata, schema markup, accessibility, internal links, and a build check. Runs an automated validation script then does page-type-specific checks.
- Before publishing or updating any blog post, career page, industry page, or /now article
- Phase 0 — runs your automated validation script, fixes all FAILs
- Phase 1 (shared) — anchor links, image paths, title/description length, OG tags, JSON-LD schema type, AEO formatting, accessibility (aria-expanded, aria-hidden), mobile layout
- Phase 2 (page-type-specific) — rules defined in your
site-checklist.mdfor each page type (blog, career, industry, /now)
PASS / FAIL / FIXED report per check.
File: distribute-social/SKILL.md
Config: CONFIG.example.md → copy to CONFIG.md
Distributes a newly published post to Reddit and LinkedIn in one run. Invokes reddit-content and linkedin-content as sub-skills (both live inside distribute-social/).
- Post slug, title, URL, key claim, target persona, best data point
Reddit drafts .md file + LinkedIn post draft with graphic suggestions.
File: distribute-outreach/SKILL.md
Config: CONFIG.example.md → copy to CONFIG.md
Finds Substack writers, journalists, and bloggers likely to reference a post's key claim. Generates personalized 3-sentence pitches and appends new contacts to a running outreach CRM file.
- Post slug, title, URL, key claim
10–15 new contacts added to {OUTREACH_CONTACTS_PATH} with personalized pitches.
File: distribute-social/reddit-content.md
Config: distribute-social/CONFIG.example.md
Finds live Reddit threads where a new post is directly relevant, then writes ready-to-paste comment drafts. No Reddit API — output is a .md file the user pastes manually. Invoked by distribute-social.
Web-searches target subreddits for threads ≤48h old. Matches thread type to a comment angle. Drafts ≤250-word comments that open with a direct answer, include one specific data point, and place the link at the end. Falls back to a standalone post draft if no live threads found.
- Post URL, title, key claim
- [Optional] Custom subreddit list (defaults in config)
{REDDIT_OUTPUT_PATH}reddit_drafts_[slug]_[date].md
File: distribute-social/linkedin-content.md
Config: distribute-social/CONFIG.example.md
Writes LinkedIn posts announcing launches, new content, or data findings. Optimizes for genuine reach — not engagement bait. Invoked by distribute-social.
- Opening earns the fold-expand with a specific fact, not a teaser
- Link near the end, after the post earns it
- Image required (every post)
- ≤3 hashtags; no hashtag wall
- No AI-writing anti-patterns: no rhetorical repetition, no em-dash pivots, no "that told us something"
- Post title, key claim, target persona, best data point, post URL
One ready-to-post LinkedIn draft (short or long form) with graphic suggestions.