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kostja94

article-page-generator

by Kostja Zhang · GitHub ↗ · v1.3.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install article-page-generator
Description
When the user wants to create, optimize, or audit a single article/post page (not the blog index). Also use when the user mentions "article page," "blog post...
README (SKILL.md)

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 Analysis2. Content Analysis3. 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:

  1. Product connection: How does this article support the product? (educate on problem, introduce features, nurture leads)
  2. Keyword basis: Target keyword from product context or keyword research — see keyword-research
  3. Content type: Blog post, guide, tutorial, news, evergreen
  4. Length: Short (\x3C1,000 words), medium (1,000–2,500), long (2,500+)
  5. 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-search not /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):

\x3Cmeta property="og:type" content="article">
\x3Cmeta property="og:article:published_time" content="2025-01-15T09:00:00Z">
\x3Cmeta property="og:article:modified_time" content="2025-02-01T14:30:00Z">
\x3Cmeta 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 \x3C 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
  • 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
Usage Guidance
This skill appears coherent and safe for its stated purpose. Before using it, be aware that it will: (1) read any project-context files in the agent workspace if present (e.g., .claude/project-context.md or .cursor/project-context.md), and (2) perform web searches and fetch competitor pages, then display those search results. If your workspace contains sensitive drafts or private product data you don't want exposed to external research output, remove or sanitize those files first. Also note the skill's manifest doesn't explicitly list the project-context paths it reads — that's a minor metadata omission, not a functional risk.
Capability Analysis
Type: OpenClaw Skill Name: article-page-generator Version: 1.3.0 The 'article-page-generator' skill bundle is a standard set of instructions for an AI agent to assist in creating and auditing SEO-optimized article pages. It provides a structured workflow for research, intent analysis, and content recommendations, referencing common SEO practices like schema markup and internal linking. The instructions to read project context files (e.g., project-context.md) are consistent with its stated purpose of providing tailored content analysis and do not exhibit signs of malicious intent or data exfiltration.
Capability Assessment
Purpose & Capability
Name/description match the instructions: the skill focuses on single-article structure, SEO, schema, and competitor analysis. It does not request credentials or external installs, which is appropriate. Minor note: SKILL.md expects the agent to read local project-context files (e.g. .claude/project-context.md or .cursor/project-context.md) but the skill's manifest does not list any required config paths — this is not dangerous but is a small metadata omission.
Instruction Scope
Runtime instructions are detailed but stay within the skill's scope: they direct the agent to extract keywords from the article, read project-context files if present, perform lightweight web searches to fetch competitor pages, and produce structured analysis and recommendations. The instructions do not ask for unrelated system files, secrets, or broad discretionary data collection. They do require the agent to display search results when research is performed.
Install Mechanism
This is an instruction-only skill with no install spec and no code files — lowest-risk install profile.
Credentials
The skill requests no environment variables, credentials, or config paths. Its runtime behaviors (reading workspace project-context files and performing web searches) are proportionate to the stated purpose.
Persistence & Privilege
always is false and the skill does not request elevated or persistent privileges. It does not modify other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install article-page-generator
  3. After installation, invoke the skill by name or use /article-page-generator
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.3.0
Batch: about-page through contact-page
v1.2.0
Automated batch sync
Metadata
Slug article-page-generator
Version 1.3.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is article-page-generator?

When the user wants to create, optimize, or audit a single article/post page (not the blog index). Also use when the user mentions "article page," "blog post... It is an AI Agent Skill for Claude Code / OpenClaw, with 178 downloads so far.

How do I install article-page-generator?

Run "/install article-page-generator" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is article-page-generator free?

Yes, article-page-generator is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does article-page-generator support?

article-page-generator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created article-page-generator?

It is built and maintained by Kostja Zhang (@kostja94); the current version is v1.3.0.

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