article-page-generator▌
kostja94/marketing-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Guides structure, SEO, and UX for individual article pages — layout, metadata, schema, technical. For article body content (intro, body, conclusion, writing), see article-content. Distinct from blog-page-generator, which covers the blog index/listing page.
Pages: Article (Single Post)
Guides structure, SEO, and UX for individual article pages — layout, metadata, schema, technical. For article body content (intro, body, conclusion, writing), see article-content. Distinct from blog-page-generator, which covers the blog index/listing page.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Output workflow: Always output in order: 0. Research Phase (keywords, search intent, competitors) → 1. Intent Analysis → 2. Content Analysis → 3. Recommendations. Do not skip steps. When Research Phase was performed via web search, show the search results and findings.
Optimization Foundation: Four Inputs
Article analysis and creation rest on four inputs. Gather or infer them before outputting recommendations:
| Input | Purpose | Source |
|---|---|---|
| Product | Product connection, features, use cases, CTA placement | project-context (Sections 1–4, 9–11); article content; web search |
| Keywords | Target keyword, primary/secondary placement | project-context Section 6; keyword-research; article |
| Article intent | Informational, commercial, transactional, navigational; drives structure, CTA, SEO depth | project-context Section 6 (target intent); article orientation; content type |
| Competitor articles | Structure to adopt, content gaps, length target, keyword opportunities | User-provided URLs; project-context Section 11; web search |
When any input is missing: Proactively ask or search. For article analysis: perform Research Phase (keyword search, search intent, competitor articles) by default — see Research Phase section. For product/keywords/intent, infer from article or prompt user to add project-context.
Before Analysis: Gather Context
1. Product / company context
Use available context to give tailored analysis:
| Source | Use for |
|---|---|
| project-context.md | Keywords (Section 6), competitors (Section 7), content strategy (Section 11), product connection |
| Article content | Extract product name, features, URLs; infer target keyword and audience |
| Web search | When analyzing a known brand: search for "[product] features", "[product] vs competitors", company positioning — use to validate product connection, suggest missing features/use cases, and improve competitor gap analysis |
If no project-context exists, infer from the article and optionally search for company/product info to enrich recommendations.
Research Phase: Keyword, Search Intent, Competitor (Required for Article Analysis)
Lightweight research for article analysis. When analyzing or auditing an article, perform searches and output the results in Section 0. Skip only if user explicitly asks to skip (e.g. "skip search").
- Keyword: Extract from article (title, H1, H2s, first 100 words); search for opportunities — see keyword-research (extract from article method)
- Search intent: Informational / Commercial / Transactional / Navigational — see keyword-research Search Intent
- Competitor articles: Fetch 2–3 top-ranking pages; analyze structure, gaps, length target — see competitor-research (Competitor Article Fetch Workflow)
Output format: See Output Format Section 0 below.
Scope
- Single article page: One post, one URL (e.g.
/blog/how-to-optimize-seo) - Not the blog index, category pages, or archive pages — see blog-page-generator for those
Initial Assessment
Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for topics, audience, keywords, and Section 11 (Content/Blog/Article Strategy).
Identify:
- Product connection: How does this article support the product? (educate on problem, introduce features, nurture leads)
- Keyword basis: Target keyword from product context or keyword research — see keyword-research
- Content type: Blog post, guide, tutorial, news, evergreen
- Length: Short (<1,000 words), medium (1,000–2,500), long (2,500+)
- Intent: Informational, commercial, problem-aware
Product-linked content: Articles should tie to the product (problem it solves, features, use cases). Avoid purely generic content with no product relevance. Link to product/feature pages naturally in conclusion or when context fits.
Article Orientations
Choose structure, SEO depth, and schema based on orientation. See content-marketing for full Article Orientations (Funding/PR, Product update, Guide, News, Evergreen), SEO-driven vs non-SEO-driven, Evergreen vs Timely.
Intent Analysis output: Orientation, primary goal, SEO vs non-SEO, Evergreen vs timely — see Output Format Section 1.
Article Page Structure
| Section | Purpose |
|---|---|
| Hero/Header | Title (H1), author, single date (see schema-markup Date display for CTR), reading time (word count ÷ 200; round up), featured image, share buttons |
| TL;DR or Key Takeaways | See article-content for content; placed after intro; supports GEO/AI citation |
| Introduction | See article-content for hook, length, keyword placement |
| Body | See article-content for QAE, paragraph length, scannability |
| Conclusion | See article-content for summary, CTA, product connection |
| Related posts | 3–6 contextual links; end-of-article recommendations |
| Author bio | E-E-A-T; credentials, photo, link to author page — see eeat-signals |
Featured Image
See image-optimization (Article / Blog hero). Same image for Schema, Open Graph, Twitter Cards; min 1200px wide, absolute URL. See open-graph, twitter-cards.
Social Sharing
- Add share buttons (X, LinkedIn, Facebook, etc.) — see social-share-generator
- Place after intro and/or end of article; sticky sidebar for long-form
- Requires Open Graph and Twitter Cards for rich previews when shared
GEO / AI Optimization
See article-content for TL;DR, Key Takeaways, QAE pattern, answer-first; generative-engine-optimization for full GEO strategy.
Long-Form (1,000+ words)
- Add table of contents (TOC) after intro — see toc-generator
- Use jump links for major sections
- Break text with images, lists, definition boxes, mini-FAQs
SEO Best Practices
Title & Meta
| Element | Guideline |
|---|---|
| Title | 55 chars; primary keyword near start; power words |
| Meta description | 150–160 chars; CTA; primary keyword |
| H1 | One per page; matches title; primary keyword naturally |
Keyword Placement
- Title: 1× primary keyword
- First 100 words: 1× primary keyword
- Body: 2–3× naturally; avoid stuffing
- At least one H2: Include primary or related keyword
Content Quality
See article-content for readability, depth, originality, word count by type. E-E-A-T: Author bio, citations, changelog, expert quotes — see eeat-signals.
Common Mistakes to Avoid
- Multiple H1s; skipping heading levels (H2→H4); keyword stuffing in headings
- Neglecting conclusion or CTA; no internal links to related content
- Walls of text; generic "click here" anchors
URL
Use url-slug-generator for slug creation. Key rules:
- Slug: 3–5 words; under 60 chars; primary keyword; lowercase, hyphens
- Example:
/blog/ai-people-searchnot/blog/ai-search-engine-finding-people-speed-discovery-outreach - Avoid: Date in path (
/blog/2025/01/15/article-title); copy-pasting full title
Date Display
See schema-markup (Date display for CTR): show only one visible date; prefer dateModified.
Schema & Open Graph
See schema-markup for Article/BlogPosting/NewsArticle type selection, required properties, JSON-LD example, and date display. Validate with Rich Results Test.
Open Graph for Articles
Use og:type: article for article pages (not website):
<meta property="og:type" content="article">
<meta property="og:article:published_time" content="2025-01-15T09:00:00Z">
<meta property="og:article:modified_time" content="2025-02-01T14:30:00Z">
<meta property="og:article:author" content="https://example.com/author/jane">
Internal Linking
| Element | Guideline |
|---|---|
| Volume | 3–5 contextual links in body + 3–6 in Related posts = 6–11 total per article |
| First paragraph | 1 link to pillar or key related content |
| Body | 2–4 contextual links; one per major section when relevant |
| Related posts | 3–6 end-of-article links; same topic cluster |
| Anchor text | Descriptive (e.g. "SEO checklist for 2025", "how to optimize meta tags"); avoid "click here", "learn more", "read more" |
| Variation | Mix exact-match, partial-match, branded anchors; avoid over-optimization |
| Orphan prevention | Every article has ≥1 internal link from hub/pillar or nav |
Outbound Links (External)
| Element | Guideline |
|---|---|
| Volume | 2–5 external links per article; cite authoritative sources |
| When to use | Statistics, research, definitions, tool comparisons, expert quotes |
| Anchor text | Descriptive (e.g. "Google's Search Quality Guidelines", "SEO study"); link to source |
| Same URL | Counts once per page for link equity; no need to repeat |
| E-E-A-T | External links to reputable sources signal trust — see eeat-signals |
References / Citations
See article-content for citation format; eeat-signals for E-E-A-T and when to include.
AI-Assisted Content
See article-content for AI-assisted content guidance; eeat-signals for E-E-A-T.
Technical
- Core Web Vitals: LCP < 1.0s on mobile
- Images: WebP, compressed; descriptive alt text; keyword in filename when natural
- IndexNow: For fast indexing of new posts
- Canonical: Self-referencing canonical on article page
Post-Publication
- Refresh: Update every 6–12 months; refresh stats, add insights
- Internal links: Add links from older posts to new articles
- Monitor: GSC indexing, rankings, Core Web Vitals
Content Analysis
When auditing or optimizing an article, apply the Content Audit Checklist. See article-content for full dimensions.
Output Format
0. Research Phase (output first, when analysis/audit is performed)
When analyzing or auditing an article, output this section before Intent Analysis. Include search sources and findings. If user asked to skip search, note that and infer from article only.
| Section | Output |
|---|---|
| Keyword Search | Primary keyword (from article or search), secondary keywords, keyword opportunities (from SERP/competitor analysis). If search was performed: query used, top results observed. |
| Search Intent | Intent for primary keyword (Informational/Commercial/Transactional/Navigational), intent for 2–3 secondary keywords, whether article content matches intent. If search was performed: SERP snippet types observed. |
| Competitor Articles | If searched: 2–3 URLs, brief structure (word count, H2s), content gaps, length target. If user provided URLs: same. See competitor-research for full methodology. If skipped: "Competitor analysis skipped." |
1. Intent Analysis (output second)
Before any recommendations, output a brief analysis:
| Dimension | Output |
|---|---|
| Orientation | Funding/PR, Product update, Guide, News, Evergreen |
| Primary goal | Brand, PR, education, product adoption, organic traffic, … |
| SEO vs non-SEO | SEO-driven / Non-SEO-driven / Hybrid |
| Evergreen vs timely | Evergreen / Timely |
| Implications | 1–2 sentences: e.g. "Low SEO priority → focus on clarity, shareability" or "SEO-driven → full keyword + GEO optimization" |
2. Content Analysis (output third)
Apply the Content Analysis table above. Output a brief assessment per dimension (✅ / ⚠️ / ❌ + one-line note).
3. Recommendations (output fourth, tailored to intent)
Assign priority to each item: P0 (critical), P1 (high), P2 (medium), P3 (nice-to-have). Output as table or list with priority prefix.
| Priority | Use when |
|---|---|
| P0 | Blocks GEO/SEO; missing core element (TL;DR or Key Takeaways, keyword in first 100 words, schema) |
| P1 | Significant impact on traffic, CTR, or conversion (title length, share buttons, CTA) |
| P2 | Improves UX or authority (related posts, author bio, internal links) |
| P3 | Polish (image optimization, readability tweaks) |
Example: [P0] Add TL;DR or Key Takeaways — GEO, AI citation
- Product connection (how article supports product; where to link) — see article-content
- Keyword (target from product context or keyword research)
- Structure for article template (hero, TL;DR or Key Takeaways, intro, body, conclusion, related, author) — content creation: article-content
- Featured image (dimensions, alt, file size, og:image alignment)
- GEO elements (TL;DR or Key Takeaways, QAE pattern) — skip or minimal for non-SEO-driven
- SEO checklist (title, meta, H1, keyword placement) — skip or minimal for non-SEO-driven
- Schema type and JSON-LD
- Internal links (3–5 in body + 3–6 Related; anchor text suggestions; avoid "click here")
- Outbound links (2–5 external; cite stats, research; anchor text for each)
- References (inline citations vs Reference section; when to add for E-E-A-T)
- Competitor analysis (when URLs provided or searched): content gaps vs top rankers, structure to adopt, length target, keyword opportunities — see competitor-research for methodology; Before Analysis to prompt user or search
Related Skills
- article-content: Article body creation; intro, body, conclusion; writing frameworks; Content Audit Checklist
- eeat-signals: E-E-A-T; author bio, citations, YMYL
- competitor-research: Content gaps, structure, length target
- blog-page-generator: Blog index/listing; article pages live within blog
- keyword-research: Keyword basis for articles
- schema-markup: Article/BlogPosting/NewsArticle schema
- howto-section-generator: HowTo step sections; HowTo schema alongside Article
- heading-structure: H1–H6 structure for article body
- content-optimization: H2 keywords, tables, lists, multimedia; word count for articles → article-content
- image-optimization: Article hero/featured image specs
- internal-links: Related posts, contextual links
- open-graph, twitter-cards: Social previews for articles
- generative-engine-optimization: GEO strategy; AI citation optimization
How to use article-page-generator on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add article-page-generator
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches article-page-generator from GitHub repository kostja94/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate article-page-generator. Access the skill through slash commands (e.g., /article-page-generator) or your agent's skill management interface.
Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›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
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share 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
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★53 reviews- ★★★★★Tariq Choi· Dec 28, 2024
article-page-generator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chaitanya Patil· Dec 24, 2024
We added article-page-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chen Huang· Dec 20, 2024
Solid pick for teams standardizing on skills: article-page-generator is focused, and the summary matches what you get after install.
- ★★★★★Isabella Robinson· Dec 20, 2024
We added article-page-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Neel Bansal· Dec 8, 2024
article-page-generator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Tariq Park· Nov 27, 2024
Useful defaults in article-page-generator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Piyush G· Nov 15, 2024
article-page-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★James Singh· Nov 11, 2024
Registry listing for article-page-generator matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Harper Park· Nov 11, 2024
article-page-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Chen Thomas· Nov 7, 2024
I recommend article-page-generator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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