agentic-seo-skill
LLM-first SEO analysis skill with 16 sub-skills, 10 specialist agents, and 89 evidence collection scripts for comprehensive SEO audits
How do I install this agent skill?
npx skills add https://github.com/reason-machines/ai-agent-skills --skill agentic-seo-skillIs this agent skill safe to install?
- Gen Agent Trust Hubfail
The skill instructions recommend installing software by piping a remote script from an unverified GitHub repository directly into a shell, which is a significant security risk. It also uses PowerShell bypass commands that lower system security settings. Additionally, because the skill processes content from arbitrary websites, it is vulnerable to indirect prompt injection where malicious data on a site could trick the agent into performing unintended actions.
- Socketwarn
1 alert: gptAnomaly
- Snykwarn
Risk: MEDIUM · 2 issues
What does this agent skill do?
Agentic SEO Skill
Skill by ara.so — AI Agent Skills collection.
The Agentic SEO Skill is an LLM-first SEO analysis framework designed for AI coding assistants and agent IDEs. It provides 16 specialized sub-skills, 10 specialist agents, and 89 Python scripts for evidence-based SEO analysis. The skill follows a reasoning-first workflow: collect evidence, analyze with LLM proof, apply confidence labels, prioritize by impact, and produce actionable plans.
Installation
Quick Install (No Cloning Required)
Linux/macOS:
# Install to all supported IDEs
curl -fsSL https://raw.githubusercontent.com/Bhanunamikaze/Agentic-SEO-Skill/main/install.sh | bash -s -- --online
# Install to Claude Code only
curl -fsSL https://raw.githubusercontent.com/Bhanunamikaze/Agentic-SEO-Skill/main/install.sh | bash -s -- --online --target claude
# Install to specific project
curl -fsSL https://raw.githubusercontent.com/Bhanunamikaze/Agentic-SEO-Skill/main/install.sh | bash -s -- --online --target all --project-dir /path/to/project
Windows (PowerShell 7+):
irm https://raw.githubusercontent.com/Bhanunamikaze/Agentic-SEO-Skill/main/install.ps1 -OutFile install.ps1
powershell -ExecutionPolicy Bypass -File .\install.ps1 --online
From Source
git clone https://github.com/Bhanunamikaze/Agentic-SEO-Skill.git
cd Agentic-SEO-Skill
# Install to Claude Code with dependencies
bash install.sh --target claude --install-deps
# Install with Playwright for visual analysis
bash install.sh --target claude --install-deps --install-playwright
Installation Targets
| Target | Location | Format |
|---|---|---|
claude | ~/.claude/skills/seo | Skill directory |
codex | ~/.codex/skills/seo | Skill directory |
cursor | <project>/.cursor/rules/seo.mdc | MDC rule |
windsurf | <project>/.windsurf/rules/seo.md | Windsurf rule |
copilot | <project>/.github/copilot-instructions.md | Repo instructions |
cline | <project>/.clinerules | Project rules |
continue | <project>/.continue/prompts/seo.prompt | Slash command |
antigravity | <project>/.agent/skills/seo | Skill directory |
Core Workflow
The skill follows an LLM-first analysis pattern:
- Collect Evidence — Use
read_url_contentMCP tool or evidence collection scripts - Analyze with LLM — Apply explicit proof and reasoning for each finding
- Label Confidence — Mark findings as
Confirmed,Likely, orHypothesis - Prioritize — Rank by impact and implementation effort
- Generate Action Plan — Produce structured, evidence-backed recommendations
All audits must follow the resources/references/llm-audit-rubric.md standard.
16 Specialized Sub-Skills
1. SEO Audit (Full Site)
Run comprehensive site-wide audits with evidence-backed scoring:
# Quick full audit with all outputs
python3 scripts/audit_runner.py https://example.com
# Outputs:
# - audit_results.json
# - audit_report.html
# - FULL-AUDIT-REPORT.md
# - ACTION-PLAN.md
Agent prompt:
Use the seo audit sub-skill to analyze https://example.com — follow the LLM audit rubric, collect evidence first with read_url_content, then reason through technical, content, and performance issues.
2. SEO Page (Single Page Analysis)
Deep analysis of individual pages:
# Fetch page content
python3 scripts/fetch_page.py https://example.com/page
# Parse HTML for SEO signals
python3 scripts/parse_html.py example_com_page.html
# Check Core Web Vitals
python3 scripts/pagespeed.py https://example.com/page
Agent prompt:
Analyze this single page for SEO: https://example.com/about — check title, meta description, headings hierarchy, internal links, schema markup, and Core Web Vitals.
3. SEO Technical
Crawlability, indexability, security, mobile-friendliness, and AI crawler policies:
# Check robots.txt policies
python3 scripts/robots_checker.py https://example.com
# Run indexability matrix (robots, meta robots, canonicals, status codes)
python3 scripts/indexability_matrix.py https://example.com
# Multi-page crawl audit
python3 scripts/crawl_audit.py https://example.com --max-depth 3
Agent prompt:
Run a technical SEO audit on https://example.com — check robots.txt, XML sitemaps, HTTPS, mobile responsiveness, JS rendering, and AI crawler access (GPTBot, ClaudeBot).
4. SEO Content
Content quality assessment with E-E-A-T framework (September 2025 Quality Rater Guidelines):
# Extract article content
python3 scripts/fetch_page.py https://example.com/article
# Run content quality checks (agent analyzes with LLM)
# Check: word count, readability, E-E-A-T signals, topical depth
Agent prompt:
Assess content quality for https://example.com/blog/post using E-E-A-T criteria — check expertise signals, author credentials, content depth, readability, and December 2025 core update alignment.
5. SEO Schema
Schema.org detection, validation, and JSON-LD generation:
# Validate existing schema markup
python3 scripts/validate_schema.py example_com.html
# Check for deprecated schema types
python3 scripts/parse_html.py example_com.html --extract-schema
Agent prompt:
Validate schema markup on https://example.com — check JSON-LD syntax, required fields, deprecated types, and suggest appropriate schema.org types (Article, Product, LocalBusiness, etc.).
Example JSON-LD generation:
# Agent generates schema based on page content
schema = {
"@context": "https://schema.org",
"@type": "Article",
"headline": "Page Title",
"author": {
"@type": "Person",
"name": "Author Name"
},
"datePublished": "2026-01-15",
"dateModified": "2026-05-27",
"image": "https://example.com/image.jpg",
"publisher": {
"@type": "Organization",
"name": "Publisher Name",
"logo": {
"@type": "ImageObject",
"url": "https://example.com/logo.png"
}
}
}
6. SEO Sitemap
XML sitemap validation and generation:
# Discover and validate sitemaps
python3 scripts/sitemap_checker.py https://example.com
# Check for issues: 404s, lastmod quality, URL limits (50,000 per file)
Agent prompt:
Audit XML sitemaps for https://example.com — check discovery (robots.txt reference), URL limits, 404s, lastmod accuracy, and sitemap index structure.
7. SEO Images
Image optimization audit (alt text, formats, lazy loading, CLS):
# Generate image inventory
python3 scripts/image_inventory.py https://example.com
# Outputs: alt text coverage, dimensions, loading behavior, LCP candidates
Agent prompt:
Analyze image SEO for https://example.com — check alt text, file formats (WebP), lazy loading, responsive images (srcset), and LCP image optimization.
8. SEO GEO (Generative Engine Optimization)
Optimize for AI Overviews, ChatGPT, Perplexity:
Agent prompt:
Optimize this content for AI search engines (ChatGPT, Perplexity, Google AI Overviews) — add clear definitions, structured facts, citations, and FAQ sections.
Pattern:
- Use concise definitions (20-30 words)
- Add structured lists and tables
- Include citations and sources
- Create FAQ sections for common queries
9. SEO AEO (Answer Engine Optimization)
Optimize for Featured Snippets, People Also Ask, Knowledge Panels:
Agent prompt:
Optimize for Featured Snippets — structure content with clear question headers, concise answers (40-60 words), and bulleted/numbered lists.
Pattern:
## What is [Topic]?
[Topic] is [concise 40-60 word definition].
### Key Benefits:
1. Benefit one
2. Benefit two
3. Benefit three
10. SEO Links
Link profile analysis — internal links, backlinks, anchor text, orphan pages:
# Extract all links from page
python3 scripts/parse_html.py example_com.html --extract-links
# Agent analyzes: internal link structure, anchor text distribution, orphan pages
Agent prompt:
Audit internal linking structure for https://example.com — identify orphan pages, check anchor text diversity, analyze link depth, and suggest hub pages.
11. SEO Programmatic
Quality gates for programmatic SEO pages:
Agent prompt:
Review programmatic SEO pages for quality — check for thin content, duplicate patterns, template issues, and unique value signals on each page.
Quality gates:
- Minimum 800 words unique content per page
- No placeholder text (e.g., "[City]", "Lorem ipsum")
- Unique titles and meta descriptions
- 3+ internal links to related pages
12. SEO Competitors
Comparison and alternatives page generation:
Agent prompt:
Generate a "Competitors" or "Alternatives" comparison page for [Product] — include feature tables, pricing comparison, use case fit, and neutral tone.
13. SEO Hreflang
International SEO and hreflang validation:
# Parse hreflang tags
python3 scripts/parse_html.py example_com.html --extract-hreflang
Agent prompt:
Validate hreflang implementation for multi-language site — check bidirectional links, correct language codes (ISO 639-1), regional variants (en-US, en-GB), and x-default fallback.
14. SEO Plan
Strategic SEO planning with topical clusters and industry templates:
Agent prompt:
Create an SEO content strategy for a SaaS product — build topical clusters, identify pillar pages, keyword themes, and internal linking structure.
Industry templates available:
- SaaS
- E-commerce
- Local Business
- Publisher/Media
- Agency
- Generic
15. SEO GitHub
GitHub repository SEO optimization:
# Generate GitHub SEO report
python3 scripts/github_seo_report.py owner/repo
# Outputs:
# - GITHUB-SEO-REPORT.md
# - GITHUB-ACTION-PLAN.md
Agent prompt:
Optimize GitHub repository SEO for [owner/repo] — improve description, add topics, enhance README structure, optimize title/headline, and benchmark against query results.
Key checks:
- Repository description (160 chars, keyword-rich)
- Topics (8-12 relevant tags)
- README structure (clear headline, features, installation)
- Social preview image
- Community health files (CODE_OF_CONDUCT.md, CONTRIBUTING.md)
16. SEO Article
Article data extraction and LLM-driven content optimization:
Agent prompt:
Extract article content and optimize — check headline, readability, keyword density, internal links, meta description, and suggest improvements.
10 Specialist Agents
The skill includes specialized agents for domain-specific analysis:
- Technical SEO Agent — Crawlability, indexability, security, mobile, JS rendering
- Content Quality Agent — E-E-A-T scoring, AI content detection
- Performance Agent — Core Web Vitals (LCP, INP, CLS)
- Schema Markup Agent — JSON-LD validation and generation
- Sitemap Agent — XML sitemap quality gates
- Visual Analysis Agent — Screenshots, above-the-fold analysis (requires Playwright)
- GitHub Analyst Agent — Repository metadata and README optimization
- GitHub Benchmark Agent — Query ranking and competitor intelligence
- GitHub Data Agent — API fallback and traffic archival
- Verifier Agent (Global) — Deduplication and contradiction suppression
Key Scripts Reference
Evidence Collection
# Fetch page with SEO crawler headers
python3 scripts/fetch_page.py https://example.com
# Output: example_com.html
# Parse HTML for all SEO signals
python3 scripts/parse_html.py example_com.html
# Extracts: title, meta, headings, links, images, schema, canonical
# Check robots.txt and crawler policies
python3 scripts/robots_checker.py https://example.com
# Multi-page crawl
python3 scripts/crawl_audit.py https://example.com --max-depth 2 --max-pages 50
Performance & Core Web Vitals
# PageSpeed Insights + Core Web Vitals
python3 scripts/pagespeed.py https://example.com
# Returns: LCP, INP, CLS scores + recommendations
# Note: Requires PAGESPEED_API_KEY environment variable
# Get free key: https://developers.google.com/speed/docs/insights/v5/get-started
Indexability & Crawlability
# Comprehensive indexability matrix
python3 scripts/indexability_matrix.py https://example.com
# Checks: robots.txt, meta robots, X-Robots-Tag, canonical, status codes, sitemaps
# Sitemap validation
python3 scripts/sitemap_checker.py https://example.com
# Validates: URL limits, 404s, lastmod, discovery
Schema Validation
# Validate JSON-LD schema
python3 scripts/validate_schema.py page.html
# Checks: syntax, required fields, deprecated types, placeholders
Report Generation
# Full audit with all outputs
python3 scripts/audit_runner.py https://example.com
# Generate HTML dashboard
python3 scripts/generate_report.py audit_results.json --output seo-report.html
# Verify findings (deduplicate + prioritize)
python3 scripts/finding_verifier.py audit_results.json
Configuration
Environment Variables
# PageSpeed Insights API key (optional but recommended)
export PAGESPEED_API_KEY=your_api_key_here
# GitHub token for repository analysis (optional)
export GITHUB_TOKEN=your_github_token_here
Script Dependencies
Install Python dependencies:
# From project root
pip install -r requirements.txt
# Or with installer flag
bash install.sh --target claude --install-deps
Core dependencies:
requests— HTTP requestsbeautifulsoup4— HTML parsinglxml— Fast XML/HTML parserplaywright(optional) — Visual analysis and screenshots
Install Playwright browsers:
playwright install chromium
# Or use installer flag
bash install.sh --target claude --install-deps --install-playwright
Common Patterns
Pattern 1: Quick Page Audit
# 1. Fetch page
python3 scripts/fetch_page.py https://example.com/page
# 2. Parse HTML
python3 scripts/parse_html.py example_com_page.html > page_data.json
# 3. Check Core Web Vitals
python3 scripts/pagespeed.py https://example.com/page > cwv_data.json
# 4. Agent analyzes JSON outputs with LLM reasoning
Agent prompt:
Analyze page_data.json and cwv_data.json — identify Critical/Warning/Pass findings, apply confidence labels, prioritize by impact, output structured action plan following llm-audit-rubric.md.
Pattern 2: Multi-Page Crawl Audit
# 1. Crawl site (respects robots.txt)
python3 scripts/crawl_audit.py https://example.com --max-depth 3 --max-pages 100 > crawl_results.json
# 2. Generate indexability matrix
python3 scripts/indexability_matrix.py https://example.com > indexability.json
# 3. Agent identifies issues: orphan pages, redirect chains, indexability blocks
Pattern 3: Schema Validation & Generation
# 1. Parse existing schema
python3 scripts/parse_html.py page.html --extract-schema > existing_schema.json
# 2. Validate
python3 scripts/validate_schema.py page.html
# 3. Agent generates improved schema based on page content and validation errors
Pattern 4: GitHub Repository SEO
# Generate full GitHub SEO report
python3 scripts/github_seo_report.py owner/repo
# Outputs:
# - GITHUB-SEO-REPORT.md (current state + benchmarks)
# - GITHUB-ACTION-PLAN.md (prioritized improvements)
Agent workflow:
- Check repository metadata (description, topics, social preview)
- Analyze README structure and keyword optimization
- Benchmark title against search results
- Suggest query-aligned title improvements
- Identify missing community health files
Pattern 5: Full Site Audit with Reports
# One command generates all outputs
python3 scripts/audit_runner.py https://example.com
# Generates:
# 1. audit_results.json (structured data)
# 2. audit_report.html (interactive dashboard)
# 3. FULL-AUDIT-REPORT.md (markdown report)
# 4. ACTION-PLAN.md (prioritized tasks)
LLM Audit Rubric
All SEO analyses must follow the standard rubric at resources/references/llm-audit-rubric.md:
Finding Format
### [Severity]: [Finding Title]
**Evidence:**
[Specific, verifiable proof — URLs, code snippets, metrics]
**Impact:**
[SEO consequence — traffic, rankings, crawlability, user experience]
**Confidence:**
- Confirmed / Likely / Hypothesis
**Fix:**
[Actionable, specific remediation steps]
**Priority:**
- Impact: High / Medium / Low
- Effort: High / Medium / Low
Severity Levels
- Critical — Blocks indexing, causes crawl errors, security issues
- Warning — Degrades SEO performance, suboptimal implementation
- Pass — Meets best practices
- Info — Opportunities, neutral observations
Confidence Labels
- Confirmed — Direct evidence (status codes, parsed HTML, API responses)
- Likely — Strong inference from multiple signals
- Hypothesis — Reasoned speculation requiring validation
Troubleshooting
Script Errors
Issue: ModuleNotFoundError: No module named 'requests'
Fix:
pip install -r requirements.txt
# Or
pip install requests beautifulsoup4 lxml
Issue: playwright._impl._errors.Error: Executable doesn't exist
Fix:
pip install playwright
playwright install chromium
Issue: PageSpeed API rate limit (403 or 429 errors)
Fix:
# Get free API key (100 queries/day)
# https://developers.google.com/speed/docs/insights/v5/get-started
export PAGESPEED_API_KEY=your_key_here
python3 scripts/pagespeed.py https://example.com
Installation Issues
Issue: Skill not detected after installation
Fix:
# Verify installation path
ls -la ~/.claude/skills/seo/
# Restart IDE
# Claude Code: restart extension
# Cursor: restart application
# Re-run installer with verbose output
bash install.sh --target claude -v
Issue: Windows PowerShell execution policy error
Fix:
# Run once per session
Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
# Then run installer
.\install.ps1 --online --target claude
Audit Quality Issues
Issue: Too many low-confidence findings
Fix:
# Run finding verifier to deduplicate and prioritize
python3 scripts/finding_verifier.py audit_results.json
# Agent: focus on Confirmed/Likely findings first, mark Hypothesis clearly
Issue: Missing evidence in audit reports
Fix:
- Always collect evidence first (
fetch_page.py,parse_html.py,pagespeed.py) - Reference specific URLs, line numbers, metric values
- Use
read_url_contentMCP tool before reasoning - Apply llm-audit-rubric.md standard for every finding
Reference Data
The skill includes up-to-date reference files (checked by CI):
- Core Web Vitals — LCP (2.5s), INP (200ms), CLS (0.1)
- E-E-A-T Framework — September 2025 Quality Rater Guidelines
- Schema.org Types — Active, restricted, deprecated lists
- Content Quality Gates — Word count minimums, readability thresholds
- Google SEO Quick Reference — Best practices snapshot
- LLM Audit Rubric — Standardized output contract
Reference freshness is validated with:
python3 scripts/reference_freshness.py resources/references --max-age-days 90
Advanced Usage
Custom Industry Strategy
# Agent generates topical cluster strategy
# Example for SaaS product:
# Pillar page: /seo-tools
# Cluster pages:
# /seo-tools/keyword-research
# /seo-tools/link-building
# /seo-tools/technical-audit
# Each cluster page links back to pillar
# Agent uses industry template from:
# resources/skills/seo-plan.md
Multi-Language Hreflang
<!-- Agent generates hreflang tags -->
<link rel="alternate" hreflang="en" href="https://example.com/page" />
<link rel="alternate" hreflang="es" href="https://example.com/es/page" />
<link rel="alternate" hreflang="de" href="https://example.com/de/page" />
<link rel="alternate" hreflang="x-default" href="https://example.com/page" />
Validation checklist:
- Bidirectional links (each page references all others)
- Correct ISO 639-1 language codes
- Regional variants (en-US, en-GB) where applicable
- x-default fallback for unmatched locales
- Self-referential link included
Programmatic SEO Quality Gates
# Agent validates programmatic pages before deployment
quality_gates = {
"min_words": 800,
"unique_title": True,
"unique_meta_description": True,
"no_placeholders": True,
"min_internal_links": 3,
"unique_content_ratio": 0.7 # 70% unique vs template
}
# Reject pages that fail gates
# Log failures for content team review
Wiki & Documentation
Full documentation available at: https://github.com/Bhanunamikaze/Agentic-SEO-Skill/wiki
Key wiki pages:
- Script Inventory — All 89 scripts with purpose notes
- Installation Guide — Detailed per-IDE setup
- Example Prompts — 50+ tested agent prompts
- Troubleshooting — Common issues and fixes
- Report Generation — Custom report templates
License
MIT License — free for commercial and personal use.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
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