Create GEO (Generative Engine Optimization) content brief based on completed research using the GEO Specialist agent.
Generates AI-optimized content briefs for Generative Engine Optimization using Princeton study methods.
/plugin marketplace add leobrival/topographic-plugins-official/plugin install leobrival-blog-kit-plugins-blog-kit-2@leobrival/topographic-plugins-officialCreate GEO (Generative Engine Optimization) content brief based on completed research using the GEO Specialist agent.
/blog-geo "topic-name"
Example:
/blog-geo "nodejs-tracing"
Note: Provide the sanitized topic name (same as used in research filename).
GEO (Generative Engine Optimization) is the academic and industry-standard term for optimizing content for AI-powered search engines. Formally introduced in November 2023 by researchers from Princeton University, Georgia Tech, Allen Institute for AI, and IIT Delhi.
Target Platforms:
Proven Results:
Source: Princeton Study + 29 industry research papers (2023-2025)
| Aspect | SEO | GEO |
|---|---|---|
| Target | Search crawlers | Large Language Models |
| Goal | SERP ranking | AI citation & source attribution |
| Focus | Keywords, backlinks | E-E-A-T, citations, quotations |
| Optimization | Meta tags, H1 | Quotable facts, statistics, sources |
| Success Metric | Click-through rate | Citation frequency |
| Freshness | Domain-dependent | Critical (3.2x impact) |
Why Both Matter: Traditional SEO gets you found via Google/Bing. GEO gets you cited by AI assistants.
Top 3 GEO Methods (Princeton Study):
Required: Research report must exist at .specify/research/[topic]-research.md
If research doesn't exist, run /blog-research first.
Delegates to the geo-specialist subagent to create comprehensive GEO content brief:
Time: 10-15 minutes
Output: .specify/geo/[topic]-geo-brief.md
Create a new subagent conversation with the geo-specialist agent.
Provide the following prompt:
You are creating a GEO (Generative Engine Optimization) content brief based on completed research.
**Research Report Path**: .specify/research/$ARGUMENTS-research.md
Read the research report and follow your Four-Phase GEO Process:
1. **Source Authority Analysis + Princeton Methods** (5-7 min):
- **Apply Top 3 Princeton Methods** (30-40% visibility improvement):
* Cite Sources (115% increase for lower-ranked sites)
* Add Quotations (best for People & Society domains)
* Include Statistics (best for Law/Government topics)
- Assess E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness)
- Check content freshness (3.2x more citations for 30-day updates)
- Score overall authority potential (X/10)
2. **Structured Content Optimization** (7-10 min):
- Create AI-parseable H1/H2/H3 outline
- Extract key facts as quotable statements
- Structure sections as questions where appropriate
- Recommend schema.org markup (Article, HowTo, FAQPage) - near-essential
3. **Context and Depth Assessment** (7-10 min):
- Verify comprehensive topic coverage
- Identify gaps to fill
- Ensure technical terms are defined
- Recommend multi-perspective coverage (pros/cons, use cases)
4. **AI Citation Optimization** (5-7 min):
- Identify 5-7 quotable key statements
- Ensure facts are clear and self-contained
- Highlight unique value propositions
- Add date/version indicators for freshness
**Output Location**: Save your GEO brief to `.specify/geo/$ARGUMENTS-geo-brief.md`
**Important**: If research quality is insufficient (< 3 credible sources) or topic structure is ambiguous, use the User Decision Cycle to involve the user.
Begin your analysis now.
After completion, verify that .specify/geo/[topic]-geo-brief.md exists and contains:
Authority Assessment: Credibility score + improvement recommendations AI-Optimized Outline: Clear H1/H2/H3 structure with question-format headings Quotable Statements: 5-7 key facts that AI can cite Context Analysis: Topic coverage assessment + gaps identified Schema Recommendations: Article, HowTo, FAQPage, etc. Metadata Guidance: Title, description, tags optimized for AI understanding Citation Strategy: Unique value propositions + formatting recommendations GEO Checklist: 20+ criteria for AI discoverability
Before proceeding to content creation, review:
The marketing agent will use your GEO brief to:
Result: Content optimized for BOTH human readers AND AI citation.
After GEO brief is approved:
/blog-marketing to create final article/blog-generate, the orchestrator will proceed automaticallyNote: For complete AI optimization, consider running BOTH /blog-seo (traditional search) AND /blog-geo (AI search).
Use /blog-geo when you need to:
For full workflow: Use /blog-generate (which can include GEO phase).
| Feature | SEO Brief | GEO Brief |
|---|---|---|
| Keywords | Primary + secondary + LSI | Natural language topics |
| Structure | H2/H3 for readability | H2/H3 as questions for AI |
| Focus | SERP ranking factors | Citation worthiness |
| Meta | Title tags, descriptions | Schema markup, structured data |
| Success | Click-through rate | AI citation frequency |
| Length | Word count targets | Comprehensiveness targets |
| Links | Backlink strategy | Source attribution strategy |
Recommendation: Create BOTH briefs for comprehensive discoverability.
If GEO brief needs adjustments, you can:
Just provide feedback and re-run the command with clarifications.
If GEO analysis fails:
"Insufficient source authority"
/blog-research with better sources"Topic structure ambiguous"
"Missing context for AI understanding"
# Research → GEO → Write
/blog-research "topic"
/blog-geo "topic"
/blog-marketing "topic" # Marketing agent uses GEO brief
# Research → SEO → GEO → Write
/blog-research "topic"
/blog-seo "topic" # Traditional search optimization
/blog-geo "topic" # AI search optimization
/blog-marketing "topic" # Marketing agent uses BOTH briefs
# Generate command can include GEO
/blog-generate "topic" # Optionally include GEO phase
Note: Marketing agent is smart enough to merge SEO and GEO briefs when both exist.
Clear Definitions
"Distributed tracing is a method of tracking requests across microservices to identify performance bottlenecks and failures."
Data Points with Context
"According to a 2024 study by Datadog, applications with tracing experience 40% faster incident resolution compared to those relying solely on logs."
Structured Comparisons
| Feature | Logging | Tracing |
|---|---|---|
| Scope | Single service | Cross-service |
| Use case | Debugging | Performance |
Question-Format Headings
How Does OpenTelemetry Compare to Proprietary Solutions?
Actionable Recommendations
"Start with 10% sampling in production environments to minimize overhead while maintaining visibility into application behavior."
Vague Claims
"Tracing is important for modern applications."
Keyword Stuffing
"Node.js tracing nodejs tracing best practices nodejs application tracing guide..."
Buried Facts
Long paragraphs with key information not highlighted
Outdated Information
Content without publication/update dates
Unsourced Statistics
"Most developers prefer X" (without citation)
Track these indicators after publication:
Tools: No established GEO tracking tools yet. Manual testing:
GEO best practices are evolving. Focus on fundamentals:
These principles will remain valuable regardless of how AI search evolves.
Ready to optimize for AI search? Provide the topic name (from research filename) and execute this command.
This GEO command is based on comprehensive research from:
Academic Foundation:
Key Research Findings:
Industry Analysis:
For full research report, see: .specify/research/gso-geo-comprehensive-research.md