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antimoron

SEO/GEO Page-Level Keyword Optimizer

by AntiMoron · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install keyword-optimize
Description
Page-level keyword optimization using Ahrefs MCP data and GEO principles. Targets both traditional search (Google) and AI-powered search (ChatGPT, Perplexity...
README (SKILL.md)

SEO/GEO Page-Level Keyword Optimization Skill

Overview

This skill drives page-level keyword optimization by combining Ahrefs MCP data with GEO (Generative Engine Optimization) principles. It targets both traditional search engines and AI-powered search (ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini).


Inputs Required

Input Source Notes
Target page URL User The specific page to optimize
Competitor URLs (3–5) User or Ahrefs Same search intent as target page
Primary keyword User or derived Main topic the page should rank for
Ahrefs MCP credentials Environment API key or MCP session

Workflow

Phase 1 — Keyword Intelligence (Ahrefs MCP)

1. keywords_explorer(seed=primary_keyword)
   → Extract: volume, KD, CPC, related_terms, questions, parent_topic

2. site_explorer(url=competitor_url, mode="organic_keywords", limit=50)
   → Repeat for each competitor
   → Collect all keywords competitors rank for on this topic

3. content_gap(target=our_url, competitors=[url1, url2, ...], mode="page")
   → Output: keywords competitors rank for that our page does NOT cover
   → Filter by: volume > 100, KD \x3C 60

Deliverable: A keyword matrix with three tiers:

Tier Type Placement
Primary Exact match, highest volume Title, H1, meta desc, first 100 words
Secondary Semantic cluster, related terms H2/H3 headers, body paragraphs
Gap keywords Missing vs. competitors New sections, FAQ, supporting content

Phase 2 — On-Page Keyword Mapping

Map keywords to page structure following this hierarchy:

\x3Ctitle>          Primary keyword (≤60 chars)
\x3Cmeta desc>      Primary + secondary keyword + CTA (≤155 chars)
\x3Ch1>             Primary keyword variant (natural language)
\x3Ch2> × N         One secondary keyword per sub-topic
First 100 words  Primary + 1 secondary keyword (natural, not forced)
Body             LSI / gap keywords distributed at ~1 per 200 words
\x3Cimg alt>        Descriptive keyword-inclusive alt text
Internal links   Anchor text = target keyword of linked page

Rules:

  • No keyword stuffing. Density is not a metric. Relevance and coverage are.
  • Each H2 owns exactly one keyword intent. Do not blend intents in a single section.
  • Internal link anchors must use the exact target keyword of the destination page.

Phase 3 — GEO Layer (AI Search Citability)

This phase targets AI engines (ChatGPT, Perplexity, Gemini, AI Overviews).

CITE Framework (one application per major section):

C — Claim     : State the answer directly in the first sentence.
I — Insight   : Add a non-obvious detail or mechanism.
T — Trust     : Cite a source, statistic, or expert reference.
E — Evidence  : Back it up with data, example, or case.

Structural requirements:

  1. Opening definition block: First 50 words must answer the primary keyword query in one authoritative sentence. This is what AI engines extract and cite.

  2. FAQ Schema: Convert Ahrefs question-type keywords into FAQ markup.

    {
      "@type": "FAQPage",
      "mainEntity": [
        {
          "@type": "Question",
          "name": "[keyword question from Ahrefs]",
          "acceptedAnswer": { "@type": "Answer", "text": "[CITE-structured answer]" }
        }
      ]
    }
    
  3. Table / List structures: AI engines prefer extractable formats. Where the content allows, convert prose into a table or bulleted list with a clear header.

  4. Factual density: Include at least 3 verifiable facts (statistics, dates, named entities) per 500 words. Vague content is not cited.


Phase 4 — Monitoring (Ahrefs API)

# Weekly page health check
results = ahrefs_api.get_organic_keywords(url=target_page, limit=100)

for kw in results:
    if kw["position"] > 10 and kw["volume"] > 200:
        trigger_reoptimize_alert(kw)

# Monthly content gap re-run
ahrefs_api.content_gap(target=our_url, competitors=competitor_list)
→ Flag any new gap keywords with volume > 300

Alert thresholds:

  • Primary keyword drops below position 10 → immediate review
  • Click share drops >20% month-over-month → full content audit
  • New gap keyword with volume >500 appears → add FAQ or new section within 2 weeks

Priority Order

Priority Action Expected Impact
P0 Content gap analysis (page vs. competitors) Highest ROI — covers missing intent fast
P0 FAQ Schema from question keywords GEO citability + featured snippet eligibility
P1 Title / H1 / H2 keyword remapping Ranking signal alignment
P1 Opening 50-word authoritative answer block AI Overview / LLM citation rate
P2 Internal link anchor text optimization Distributes PageRank to target keywords
P2 Alt text keyword coverage Image search + accessibility
P3 API-driven ranking monitor + alerts Catch regressions early

Reference Projects

Project Stars Use
AgriciDaniel/claude-seo ~7k 25 sub-skills + 18 sub-agents, GEO/AEO, schema, semantic clustering
serpapi/awesome-seo-tools ~863 Tool discovery: keyword research, rank tracking, GEO trackers
teles/awesome-seo ~600+ Reference links for keyword research fundamentals
amplifying-ai/awesome-generative-engine-optimization ~300+ GEO methodology, AI citability patterns
aaron-he-zhu/seo-geo-claude-skills ~51 CORE-EEAT + CITE frameworks, rank tracking skills

Ahrefs MCP Endpoints Used

Endpoint Phase Purpose
keywords_explorer 1 Volume, KD, related terms, questions
site_explorer 1 Competitor organic keyword lists
content_gap 1, 4 Missing keyword identification
get_organic_keywords 4 Page ranking health monitoring
rank_tracker 4 Position trend over time
Usage Guidance
Install this only if you intend to use Ahrefs-backed SEO analysis. Avoid using it with confidential, unpublished, internal, or embargoed URLs unless your organization approves sending page, keyword, and competitor information to Ahrefs, and use a scoped Ahrefs API key where possible.
Capability Tags
requires-sensitive-credentials
Capability Assessment
Purpose & Capability
The documented capability matches the stated purpose: page-level SEO/GEO keyword research, competitor analysis, content-gap analysis, keyword mapping, FAQ schema, and rank monitoring using Ahrefs data.
Instruction Scope
The invocation text is broad enough to trigger for general search-visibility optimization, so users should invoke it intentionally when they want Ahrefs-backed keyword analysis.
Install Mechanism
The artifact contains only Markdown files and declares an AHREFS_API_KEY environment requirement; there are no executable installers, bundled dependencies, hidden scripts, or package install steps.
Credentials
An Ahrefs API key and external Ahrefs/MCP queries are proportionate for the SEO workflow, but the artifact could more clearly disclose that target URLs, competitor URLs, keywords, and derived analysis may leave the environment.
Persistence & Privilege
The monitoring section describes weekly and monthly checks conceptually, but the artifact does not implement a scheduler, background worker, persistence mechanism, privilege escalation, or destructive behavior.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install keyword-optimize
  3. After installation, invoke the skill by name or use /keyword-optimize
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Page-level keyword optimization for both classic and AI-powered search. - Implements Ahrefs MCP-driven keyword research and competitive gap analysis. - Structures keyword mapping by search intent (primary, secondary, gap) for all key page elements (title, meta, H1, H2, body, alt text, internal links). - Adds Generative Engine Optimization (GEO) practices for increased AI engine citability, including CITE framework and extractable content formats. - Generates FAQ schema from question-type keywords for enhanced search features. - Includes automated monitoring and alerting for ranking drops and new keyword gaps using Ahrefs API.
Metadata
Slug keyword-optimize
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is SEO/GEO Page-Level Keyword Optimizer?

Page-level keyword optimization using Ahrefs MCP data and GEO principles. Targets both traditional search (Google) and AI-powered search (ChatGPT, Perplexity... It is an AI Agent Skill for Claude Code / OpenClaw, with 23 downloads so far.

How do I install SEO/GEO Page-Level Keyword Optimizer?

Run "/install keyword-optimize" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is SEO/GEO Page-Level Keyword Optimizer free?

Yes, SEO/GEO Page-Level Keyword Optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does SEO/GEO Page-Level Keyword Optimizer support?

SEO/GEO Page-Level Keyword Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created SEO/GEO Page-Level Keyword Optimizer?

It is built and maintained by AntiMoron (@antimoron); the current version is v1.0.0.

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