Guides on-page content optimization: word count, heading keywords, keyword density vs stuffing, multimedia, tables, and lists. Complements heading-structure (structure) and content-strategy (planning).
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncontent-optimizationExecute the skills CLI command in your project's root directory to begin installation:
Fetches content-optimization from kostja94/marketing-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate content-optimization. Access via /content-optimization in your agent's command palette.
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.
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Guides on-page content optimization: word count, heading keywords, keyword density vs stuffing, multimedia, tables, and lists. Complements heading-structure (structure) and content-strategy (planning).
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.
Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for target keywords and content type.
Identify:
Google does not rank by word count. Length should match search intent and topic depth. A 1,000-word post that satisfies intent can outrank a 3,000-word thin piece.
For article word count by type (news, how-to, listicle, pillar, etc.), see article-content. Generic ranges:
| Content type | Word count | Notes |
|---|---|---|
| News / announcements | 300–600 | Time-sensitive; concise |
| Standard articles / how-tos | 1,000–1,500 | Single topic; actionable |
| Listicles / guides | 1,200–2,000 | "Top 10," "Best X" |
| Pillar / cornerstone | 2,000–3,500+ | Comprehensive; cluster hub |
| Practice | Purpose |
|---|---|
| Descriptive H2s | Search engines understand context; users scan |
| Answer-first | Place direct answer in first 40–50 words after H2 for Featured Snippets; see featured-snippet |
| Keyword variation | Use related terms; avoid repeating exact phrase in every H2 |
| Logical flow | H2s outline the article; support topical authority |
| Term | Meaning |
|---|---|
| Keyword density | (Keyword count / Total words) × 100; a metric, not a ranking factor |
| Keyword stuffing | Excessive, unnatural repetition to manipulate rankings; black-hat |
| Practice | Purpose |
|---|---|
| Alt, file names, captions | See image-optimization for full image SEO (alt, format, responsive, lazy loading, image sitemap, LCP, captions for Featured Snippets) |
| Original over stock | Unique images signal E-E-A-T — see eeat-signals |
Content placement: Put images near relevant text; captions support snippet thumbnails. See image-optimization for captions; featured-snippet for snippet context.
| Practice | Purpose |
|---|---|
| Embed + metadata | VideoObject schema, video sitemap, thumbnail; see video-optimization |
| YouTube | Google prioritizes YouTube in search; GEO citation; see youtube-seo, generative-engine-optimization |
| Featured Snippet (video) | Video schema; timestamps/chapters; see featured-snippet |
<table>, <thead>, <tbody>, clear column headers| Type | Use case | SEO / Snippet |
|---|---|---|
Ordered (<ol>) |
Steps, rankings, sequences, "Top 10" | List snippets (~19% of Featured Snippets); how-to; see featured-snippet |
Unordered (<ul>) |
Non-sequential items, features, options | Bullet snippets; definitions, options |
Best practices:
<ol> and <ul>; avoid divs styled as listsAnswer-first (direct answer in first 40–60 words after H2) supports both Featured Snippets and GEO. For article-level GEO (TL;DR, Key Takeaways, QAE pattern), see article-content and generative-engine-optimization. For Featured Snippet formats and optimization, see featured-snippet.
For article content audit (hook, QAE, product connection, CTA, references, gaps), see article-content. This skill covers generic content optimization (H2 keywords, multimedia, keyword density).
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
kostja94/marketing-skills
kostja94/marketing-skills
kostja94/marketing-skills
kostja94/marketing-skills
kostja94/marketing-skills
kostja94/marketing-skills
content-optimization is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
content-optimization fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend content-optimization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
content-optimization has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: content-optimization is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added content-optimization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in content-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for content-optimization matched our evaluation — installs cleanly and behaves as described in the markdown.
We added content-optimization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in content-optimization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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