Quick start (5 steps): Seed keywords > Expand with tools/autocomplete > Classify intent for each keyword > Tri-score (organic + AEO + GEO) > Cluster by topic with surface annotations. See the common tasks below for details.

• Organic blue links (SEO) - traditional rankings on Google, Bing, etc.
• Answer engine features (AEO) - featured snippets, People Also Ask, voice results
• AI-generated citations (GEO) - Google AI Overviews, ChatGPT Search, Perplexity

aeo-optimization

geo-optimization

• Wants to find keywords for a new website, product page, or blog
• Asks to analyze search intent for a keyword list
• Needs to group keywords into topic clusters or content pillars
• Wants to discover competitor keyword gaps or ranking opportunities
• Asks to find long-tail variations of a seed keyword
• Needs to prioritize a list of keywords by opportunity or difficulty
• Wants to understand what SERP features appear for a target keyword
• Asks to detect keyword cannibalization across existing pages
• Wants to evaluate keywords for snippet opportunity or featured snippet potential
• Asks to assess AI Overview presence for target keywords
• Needs a tri-surface keyword report scoring organic, AEO, and GEO opportunity
• Wants to understand which keywords AI search engines answer vs. defer

• Paid search (PPC/Google Ads) bid strategy - ad-specific match types, Quality Scores, and CPC optimization are a different domain
• Brand naming or tagline development - that is copywriting, not search research
• Formatting content to win snippets or PAA - that is

  aeo-optimization

• Making content more citable by AI engines - that is

  geo-optimization

1. Search intent is more important than volume - A keyword with 500 monthly searches and clear transactional intent will drive more revenue than a 50,000-search keyword that is purely informational. Always qualify intent before qualifying volume.
2. Cluster keywords by topic, not individual pages - One page should own a cluster of semantically related terms. Building one page per keyword creates duplication, splits authority, and fragments the user experience.
3. The SERP + AI Overview is the source of truth - No tool tells you more about what Google wants to rank than the current top 10 results and whether an AI Overview fires. Content type, length, format, featured snippet presence, and AI Overview citations all reveal the implicit standard for a keyword.
4. Long-tail keywords convert better - Longer, more specific queries have lower volume but higher purchase intent and lower competition. A content strategy built on long-tail clusters outperforms chasing high-volume head terms in most niches.
5. Competitor gaps reveal the fastest wins - Finding keywords where competitors rank in positions 4-15 (or not at all) is faster than trying to beat them on keywords where they dominate. Gaps are the entry points.
6. Every keyword has three surfaces to evaluate - A keyword that looks mediocre for organic ranking may have excellent snippet opportunity (AEO) or strong AI citation potential (GEO). Evaluating all three surfaces prevents blind spots and reveals non-obvious wins that single-surface research misses.
7. Research and optimization are separate phases - This skill identifies WHAT to target and WHERE the opportunity is. Optimization (HOW to format for snippets, HOW to boost AI citations) is a downstream activity handled by

   aeo-optimization

   and

   geo-optimization

   . Do not mix phases - complete research before starting optimization.

1. Check modifiers first - Words like "buy", "order", "coupon", "discount" signal transactional. Words like "best", "top", "review", "vs", "alternative" signal commercial investigation. Words like "how", "what", "why", "guide", "tutorial" signal informational. Brand name only = navigational.
2. When modifiers are absent, check the SERP - Look at the top 3 results. Are they product pages, comparison articles, definitions, or brand homepages? The content type Google rewards reveals the intent.
3. Assign a primary intent and note a secondary if relevant - Many keywords blend types. "Best project management software" is primarily commercial investigation with transactional secondary (the user may click through to pricing).

keyword | intent | confidence | content_type | snippet_type | ai_overview_present

references/search-intent-mapping.md

1. Generate variants - Use a keyword tool to pull: questions (People Also Ask), autocomplete suggestions, related searches, and lexical variants. For the seed "project management software", variants include "best project management tools", "project management app for teams", "free project management software", etc.
2. Group by SERP overlap - Keywords that return the same top-ranking URLs belong in the same cluster. If "project management software" and "task management tool" return 6 of the same top-10 results, one page can rank for both.
3. Identify the primary keyword - The one with the highest traffic potential becomes the primary term (used in title, H1, URL). All others are secondary terms woven into subheadings and body copy.
4. Name the cluster - Give it a descriptive label: "project management software - top-of-funnel commercial". This label drives content brief decisions.
5. Annotate with dominant surface - Score the cluster's keywords using tri-surface scoring and assign a surface label: [ORG], [AEO], [GEO], or [AEO+GEO]. This tells the content team which optimization approach to take after writing.

references/keyword-clustering.md

1. Gather raw data - For each keyword, collect: search volume, traffic potential, KD, SERP features present, featured snippet format and holder, PAA count, and AI Overview presence (check Google, optionally ChatGPT Search and Perplexity). See

   references/tool-specific-workflows.md

   for tool-by-tool data collection steps.
2. Score organic (0-10) - Based on traffic potential, KD inversion, intent-business alignment, and content gap existence.
3. Score AEO (0-10) - Based on snippet presence, format match, PAA count, voice search likelihood, and current holder strength. Score 0 for navigational and most transactional keywords where snippets don't fire.
4. Score GEO (0-10) - Based on AI Overview trigger, citation density, query type match, entity relevance, and content uniqueness. Score 0 when no AI Overview fires.
5. Calculate composite - Sum the three scores (0-30). Apply business-goal weighting if needed.
6. Assign priority surface - Highest-scoring surface becomes the priority. If two are within 2 points and both above 5, mark as dual-surface opportunity.

references/tri-surface-scoring.md

keyword | intent | organic_score | aeo_score | geo_score | composite | priority_surface

1. Pull keyword rankings for 3-5 competitors using a tool (Ahrefs, Semrush). Export keywords where competitor is in positions 1-20.
2. Filter out keywords where your site already ranks positions 1-5 (already winning).
3. Filter for keywords matching your target intent.
4. Sort by traffic potential descending.
5. New: Surface gap analysis - For the top 50 gap keywords, check whether they trigger featured snippets and AI Overviews. A keyword gap where the competitor ranks organically but doesn't hold the snippet or isn't cited by AI is a multi-surface gap - you can potentially win the snippet or AI citation even if the organic position takes time to capture.
6. Cross-reference with your content inventory. Existing pages that can be optimized are quick wins; missing pages are content creation opportunities.

references/tool-specific-workflows.md

• Question modifiers: "how to", "what is", "why does", "when should"
• Qualifier modifiers: "for small business", "for beginners", "without X", "with Y"
• Comparison modifiers: "vs", "alternative to", "better than", "instead of"
• Location modifiers: city, region, "near me", "in [country]"
• Feature modifiers: "free", "open source", "enterprise", "API", "integration"

• Question-format long-tails ("how to X for Y") score high on AEO (snippet targets)
• Comparison long-tails ("X vs Y for Z") score high on GEO (AI engines love comparisons)
• Feature/qualifier long-tails ("X with API for enterprise") are usually organic-only
• Location long-tails are almost always organic-only (local pack, not snippets or AI)

1. Executive summary (1 paragraph) - Total keywords analyzed, top clusters, dominant surface opportunity, and 3 biggest findings.
2. Intent distribution - Pie chart or table showing the breakdown of informational, commercial, transactional, and navigational keywords in the dataset.
3. Surface opportunity map - Table showing how many keywords have their priority surface as organic, AEO, GEO, dual, or tri. This reveals whether the overall strategy should lean toward traditional SEO, snippet optimization, or AI citation.
4. Top keyword clusters - For each cluster: name, primary keyword, keyword count, average composite score, dominant surface, and recommended content type.
5. Quick wins - Keywords where you have the best ratio of opportunity to effort: striking-distance organic keywords (positions 5-15), snippet-eligible keywords with no current holder, and AI Overview queries citing weak sources you can displace.
6. Content recommendations - Map clusters to content calendar items: new pages, existing pages to optimize, FAQ additions, and comparison articles to create.
7. Full keyword data - Appendix table with all keywords and their scores. Use the spreadsheet template from

   references/tool-specific-workflows.md

   .

site:yourdomain.com "keyword phrase"

• Two pages ranking for the same query: Check which page Google prefers (higher avg. position). The preferred page keeps the keyword; the other page is re-optimized for a different term or redirected.
• Rankings oscillating week to week: Classic cannibalization signal. Consolidate the weaker page's content into the stronger one via a 301 redirect.
• New page tanked the ranking of an existing page: Re-differentiate the new page's focus term or merge it back into the original.
• Snippet cannibalization: If two of your pages alternate holding the featured snippet for the same query, Google may drop both. Consolidate to ensure one definitive page owns the snippet-eligible answer.

1. Traffic potential and search volume diverge most on commercial keywords - A keyword with 300 monthly searches may be the primary term for a page that also ranks for 40 related variants, giving it 8,000 monthly visits. Conversely, a 10,000-volume head term may have traffic potential of only 6,000 because ranking page 1 earns only a small CTR share. Always pull traffic potential from your tool (Ahrefs "TP", Semrush "Traffic"), not raw volume.
2. SERP feature presence changes by location, device, and login state - An AI Overview you see in a logged-in US Chrome session may not fire in an incognito session or in another country. Always verify SERP features in incognito mode and, where relevant, from the target country using a VPN or tool like SERP API, before assigning AEO or GEO scores.
3. Keyword cannibalization diagnosis is wrong if you use position average - Google Search Console averages positions across all queries and dates. Two pages fighting for the same query may each show position 8 in the average, but the reality is one shows at 3 and the other at 15, alternating week by week. Filter GSC by specific queries and look for multiple pages appearing or for high impression/low click patterns on the same query across different pages.
4. Tri-surface scoring becomes meaningless if you score GEO for navigational queries - Navigational queries ("brand login", "product dashboard") almost never trigger AI Overviews. Assigning any GEO score above zero to navigational keywords inflates composite scores and misdirects content effort. GEO score must be zero unless you have verified an AI Overview fires for that query.
5. Keyword clusters built from tool "related keywords" lists ignore SERP overlap - Tool-suggested related keywords group by semantic similarity, not by whether Google actually returns the same URLs for both queries. Two semantically similar keywords may trigger completely different SERPs (different content types, different competition). Validate cluster membership by checking that 5+ of the top 10 results overlap between the keywords.

references/

• references/search-intent-mapping.md

  - Deep dive into the four intent types, classification signals, intent-to-content-type matrix, intent-to-surface mapping for AEO and GEO, AI Overview intent patterns, and how to validate intent assumptions from SERP data. Load when classifying a keyword list or writing a content brief.

• references/keyword-clustering.md

  - Methods for clustering keywords (semantic, SERP-based, modifier-based, surface-aware), building pillar-and-spoke topic clusters, surface-aware cluster annotation, and tooling options. Load when building a cluster or planning a content architecture.

• references/tri-surface-scoring.md

  - Complete scoring rubrics for organic (0-10), AEO (0-10), and GEO (0-10) opportunity scores, composite scoring, business-goal weighting, three worked examples, and limitations. Load when scoring keywords or producing a tri-surface keyword research report.

• references/tool-specific-workflows.md

  - Step-by-step workflows for Ahrefs, Semrush, Google Search Console + free tools, and ChatGPT/Perplexity manual audits. Includes spreadsheet template with columns, formulas, and conditional formatting. Load when performing hands-on keyword research with specific tools.

On first activation of this skill in a conversation: check which companion skills are installed by running

ls ~/.claude/skills/ ~/.agent/skills/ ~/.agents/skills/ .claude/skills/ .agent/skills/ .agents/skills/ 2>/dev/null

. Compare the results against the

recommended_skills

field in this file's frontmatter. For any that are missing, mention them once and offer to install:

npx skills add AbsolutelySkilled/AbsolutelySkilled --skill <name>

Skip entirely if

recommended_skills

is empty or all companions are already installed.