Fetches aeo-optimization from alinaqi/claude-bootstrap and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/aeo-optimization
Restart Cursor to activate aeo-optimization. Access via /aeo-optimization in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
┌────────────────────────────────────────────────────────────────┐
│ THE GREAT DECOUPLING │
│ ──────────────────────────────────────────────────────────── │
│ Impressions ≠ Clicks anymore. │
│ AI engines compile answers from multiple sources. │
│ More buyer journey happens inside chat experiences. │
│ 58% of Google searches = zero clicks (AI overviews). │
├────────────────────────────────────────────────────────────────┤
│ THE OPPORTUNITY │
│ ──────────────────────────────────────────────────────────── │
│ Shape what AI engines say about your category and product. │
│ Get cited as the authoritative source. │
│ Best answer > Best page ranking. │
└────────────────────────────────────────────────────────────────┘
Key Stats:
70% of consumers use ChatGPT for searches
47% of Google queries show AI overviews
Average ChatGPT prompt: 23 words (vs 4.2 for Google)
AEO market: $886M (2024) → $7.3B (2031)
How AI Engines Choose Answers
AI engines use three main signals to select content for answers:
1. Consensus
Facts that appear across multiple credible sources get trusted and reused.
How to build consensus:
Repeat key facts consistently across your own pages
Use same terminology as industry leaders
Link to and from authoritative external sources
Create internal content clusters that reinforce each other
2. Information Gain
Net-new insight beats generic advice. AI engines prefer content that adds value.
How to add information gain:
Original research and data
Concrete examples with specifics
Clear point of view (not fence-sitting)
Expert quotes with credentials
Case studies with metrics
3. Entities & Structure
Clear entities and tidy structure reduce ambiguity and boost quotability.
How to optimize structure:
Use semantic triples (Subject → Verb → Object)
Clear headings with entity names
Schema markup (Article, FAQ, Product)
Short, scannable paragraphs (2-4 sentences)
Semantic Triples (Critical for AEO)
What they are: Compact facts that AI engines (and humans) can't misread.
Pattern:[Subject][verb][object].
Examples
✅ GOOD (clear triples):
- HubSpot CRM syncs contact and company data.
- Lead Scoring assigns priority based on engagement.
- Workflows trigger email sequences from events.
❌ BAD (vague, no clear entity):
- The system helps with various tasks.
- It can do many things for users.
- This improves overall performance.
Triple Checklist
For every key claim, ask:
Is the subject a clear entity (product, feature, brand)?
Is the verb specific and active?
Is the object concrete and measurable?
Paragraph Pattern (Feature → How → Outcome)
Every substantive paragraph should follow this structure:
[Feature] helps [User/Role] with [Job].
It [mechanism/inputs] to [process].
Teams see [metric/result] in [timeframe/context].
Triples:
- [Subject] [verb] [object].
- [Subject] [verb] [object].
Example
Lead Scoring helps sales teams prioritize prospects. It combines
page views, email engagement, and firmographic data to assign a
numeric score, then auto-enrolls high scorers into follow-up
sequences. Reps focus on qualified accounts and book 40% more
meetings.
- Lead Scoring assigns scores from engagement data.
- High scorers trigger automated follow-up sequences.
Page Templates
Template 1: Category Explainer
Goal: Define the category, tie it to your product, earn citations.
# What is [Category]? — [1-2 line value promise]## What is [Category]? (~80 words)[Plain definition in everyday language. Name adjacent entities.]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
## Why it matters now (~60 words)[One paragraph. Mention shift to answers over links; tie to buyer outcomes.]
## How to apply it (3-5 bullets)- [Action 1]
- [Action 2]
- [Action 3]
## FAQ**Q: [Question]?**A: [~1 sentence answer]
**Q: [Question]?**A: [~1 sentence answer]
**Q: [Question]?**A: [~1 sentence answer]
---**Links:** [Category hub] | [Product/Feature] | [Credible source 1] | [Credible source 2]
**CTA:** [Demo / Template / Signup]
**Schema:** Article + FAQ. Author + last updated.
Template 2: Product & Feature Page
Goal: Clarify capability, fit, and next step; reinforce category linkage.
# [Product/Feature] — [Outcome in 3-5 words]**[Product/Feature] enables [Outcome] for [User/Role].**## [Feature Area 1][2-4 sentences using Feature → How → Outcome]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
## [Feature Area 2][2-4 sentences using Feature → How → Outcome]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
## [Feature Area 3][2-4 sentences using Feature → How → Outcome]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
## FAQ**Q: [Question]?**A: [~1 sentence]
**Q: [Question]?**A: [~1 sentence]
**Q: [Question]?**A: [~1 sentence]
---**Links:** Back to [Category Explainer] | Forward to [Demo/Trial]
**Proof:** [Benchmark/Analyst/Customer proof]
**Notes:** Requirements/limits (pricing tier, integrations)
**Schema:** Article + FAQ. Author + last updated.
Template 3: Comparison / Alternatives Page
Goal: Help readers decide with clear criteria; earn fair citations.
# [Product] vs. [Alternative] — Which fits [Use case]?## Comparison Table| Criterion | [Product] | [Alt A] | [Alt B] | Source ||-----------|-----------|---------|---------|--------|| [Feature/Limit] | [value] | [value] | [value] | [link] || [Requirement] | [value] | [value] | [value] | [link] || [Best for] | [value] | [value] | [value] | [link] |*Source-back all claims in the table or footnotes.*## Fit Statements1.**[Product]** suits [Team/Use case] when [Condition].
2.**[Alt A]** fits [Team/Use case] when [Condition].
3.**[Alt B]** works for [Team/Use case] when [Condition].
---**Links:** [Category Explainer] | [Feature pages]
**CTA:** [Try / Demo / Talk to Sales]
**Schema:** Article. Author + last updated.
Template 4: Use Case / Industry Page
Goal: Connect product to outcomes in a context readers recognize.
# [Industry/Use Case] — [Outcome KPI]**Teams reduce [Metric] by [Y%] in [Timeframe].**## Mini Case Study[Company/Role] used [Product/Feature] to [Action], resulting in
[Metric improvement] within [Timeframe].
## How It Works### [Feature 1][Feature → How → Outcome paragraph]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
### [Feature 2][Feature → How → Outcome paragraph]
Triples:
1.[Subject] [verb] [object].
2.[Subject] [verb] [object].
## Who Uses This**Roles:** [Role 1], [Role 2], [Role 3]
**Workflows:** [Workflow 1], [Workflow 2]
**Integrations:** [Integration 1], [Integration 2]
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition
✗ Don't
−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture
💡 Pro Tips
★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
1Basic: user stories, feature specs, status updates
