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Article Content

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kostja94
article-content

When the user wants to write, generate, or create article body content—blog post body, long-form content, how-to guide, listicle. Also use when the user mentions "write article," "article content," "blog post content," "article body," "long-form content creation," "generate article," "article draft," "how-to guide content," "listicle content," "information gain," or "content density." For single post page structure, schema, and SEO metadata, use article-page-generator. For blog index/listing page, use blog-page-generator. For short ad, landing, or email copy, use copywriting.

Overview

Publisherkostja94
Repositorymarketing-skills
Skill namearticle-content
Stars
979
Forks
137
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kostja94 on GitHub. Read the source before you install it.

Installation

Install the Article Content AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kostja94/marketing-skills.git /tmp/marketing-skills
mkdir -p .claude/skills
cp -r /tmp/marketing-skills/skills/content/article .claude/skills/article-content
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Article Content in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Article Content on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Article Content is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Content: Article Content

Guides creation of article body content—the actual text (intro, body, conclusion) for blog posts, guides, and long-form pieces. Focus on what to write. For where it goes (page structure, schema, metadata), see article-page-generator. For short conversion copy (ads, landing pages, CTAs), see copywriting.

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.

Scope

  • Article body: Introduction, body sections, conclusion, CTA
  • Content structure: Hook, QAE pattern, paragraph length, scannability
  • Word count: By article type and search intent
  • Writing frameworks: AIDA, PAS, BAB applied to articles
  • GEO elements: TL;DR, Key Takeaways, answer-first

Article Types & Word Count (2025)

Quality over length: Google prioritizes comprehensive coverage of search intent, not word count. Match length to topic depth and intent.

TypeWord countUse case
News / announcements300–600Product updates, breaking news, FAQs
Short-form500–800Landing pages, product pages (scannable)
Standard articles / how-tos1,000–1,500Single topic; actionable; listicles
Listicles1,200–2,000"Top 10," "Best X"; numbered lists boost CTR ~70%
Cluster articles800–2,500Subtopic; links to pillar
Pillar / cornerstone2,000–3,500+Comprehensive; cluster hub; 6–12 sections
Competitive keywords1,800–2,500Page-one SEO posts avg ~2,400 words

Intent-based (Google 2025): Validate 1,200–2,000; Explore 2,000–3,500; Compare 600–1,200; Do 900–1,500; Know 300–800. Informational ~40% longer than transactional.

Avoid: Under 300 words (thin); over 7,000 (often underperforms due to reduced focus).

Content Creation Workflow

Four Inputs

Article content rests on four inputs. See article-page-generator for full workflow.

InputPurpose
ProductConnection, features, CTA placement
KeywordsTarget keyword, primary/secondary
Article intentInformational, commercial, transactional
Competitor articlesStructure to adopt, content gaps, length target

Information Gain (Content Density Over Word Count)

Information gain = net new information a page provides beyond what exists in top-ranking results. Google evaluates unique value, not comprehensiveness. Content density (unique entities, data points, insights per 100 words) matters more than word count. Skyscraper Technique (longer = better) no longer differentiates; AI made comprehensiveness cheap.

Four sources of information gain:

  • Counter-narratives: Why "best practice" fails in certain contexts; evidence-backed
  • Temporal freshness: Data or developments after competitors' content and LLM cutoff
  • SME perspectives: Direct quotes, practitioner experience; not repackaged advice
  • Proprietary data: Original surveys, internal benchmarks, user behavior patterns

Avoid consensus content: Restating common facts across top 10 results = zero information gain. Audit SERP before writing; list the "consensus layer"; identify gaps (unanswered questions, outdated data, underserved segments). Lead with what is new; structure answer-first.

Density check: Count unique data points, original insights, specific claims. If ratio of new information to word count is low, cut filler. High-density content (800-1,500 words with 3+ original points) often outperforms long rehashed guides.

TL;DR or Key Takeaways (GEO)

Choose one; place after intro. Content with these elements tends to be cited more frequently by AI engines.

FormatSpec
TL;DR50–100 word bold summary paragraph
Key Takeaways5–7 bullet points

See generative-engine-optimization for full GEO strategy.

Introduction

Length: 40–120 words; 2–3 paragraphs. Readers decide in ~8 seconds; hook must work instantly.

ElementGuideline
HookFirst 1–2 sentences: pain point, stat, or question; curiosity gap; specific data or contrarian fact
Primary keywordIn first 100 words
ExpectationsSet what reader will learn

Hook types: "You're doing X wrong"; "97% of Y…"; bold question; challenge assumption. Well-crafted hooks boost CTR 30–50%.

Body

ElementGuideline
QAE patternQuestion (H2) → Answer (2 sentences) → Evidence (data, examples, lists)
Answer-firstDirect answer in first 40–60 words after each H2
Answer blocks100–200 words per section; direct answer + context + evidence
Paragraph length40–80 words; 2–4 sentences; avoid walls of text
Break long blocksLists, H3s, images, callout boxes every 2–3 paragraphs
ScannabilityFront-load key info (F-pattern); bold key phrases; one idea per paragraph

Long-form (1,000+ words): Place engagement hooks every 500–600 words; mix 40–50% explanatory text, 20–25% examples, 10–15% data, 5–10% visuals.

Conclusion

Summary + CTA: newsletter signup, related content, product (link to product/feature when relevant). Product-linked content ties to product naturally.

Product Connection

Articles should tie to the product (problem it solves, features, use cases). Avoid purely generic content. Link to product/feature pages naturally in conclusion or when context fits.

Writing Frameworks

Apply copywriting frameworks to article structure. See copywriting for full PAS, AIDA, BAB.

FrameworkArticle use
AIDAIntro (Attention); body (Interest, Desire); conclusion (Action/CTA)
PASHow-to guides: Problem in intro; Agitation in body; Solution throughout
BABCase studies, transformation: Before → After → Bridge

Choose by audience: AIDA for ready-to-buy; PAS for pain-driven; BAB for transformation seekers.

Article Headlines

See copywriting for headline formulas (How to, Number, Problem→Solution). For article titles specifically:

  • Length: 50–60 chars; see title-tag
  • Primary keyword near start
  • Numbers and power words boost CTR ~36%

References & Citations

ScenarioPractice
Data or statisticsCite inline (e.g. "According to Source, 72% of…") or in References section
Expert quotesAttribute; link to source
Reference sectionFor 5+ citations; list at end before Related posts
FormatInline links preferred; numbered refs [1], [2] for academic-style

See eeat-signals for E-E-A-T, author bio, citations, YMYL.

Content Quality

ElementGuideline
ReadabilityGrade 8–10 (Flesch-Kincaid); short sentences, clear language
DepthMatch type; comprehensive coverage over padding
OriginalityUnique angle, data, examples; avoid thin or rehashed content
Information gainWhat does this add that top 10 results don't? Counter-narrative, fresh data, SME quote, or proprietary insight
E-E-A-TAuthor bio, citations, expert quotes — see eeat-signals

Content Audit Checklist

When auditing or optimizing article content:

DimensionCheck
HookIntro opens with pain point, stat, or question?
Keyword in first 100 wordsPrimary keyword present?
QAE patternH2s as questions? Answer-first (40–60 words) in each section?
Word countMatches type? (300–600 news, 1,000–2,500 cluster, 2,500+ pillar)
Paragraph length40–80 words per paragraph? No walls of text?
Product connectionTies to product? Natural links to features/pricing?
CTAPlacement (conclusion, mid-article); clarity; product link
ReferencesData/stats cited? Reference section for 5+ citations?
GapsWhat do top-ranking articles cover that this misses?
Information gainAt least one of: counter-narrative, fresh data, SME perspective, proprietary data? Or consensus rehash?

See competitor-research for competitor analysis; article-page-generator for page structure and metadata.

AI-Assisted Content

When content is AI-assisted: human review before publish; verify facts and add citations; original insights or data; avoid generic phrasing. See eeat-signals for E-E-A-T and AI content guidance.

Output Format

  • Outline (H2s with keyword placement)
  • TL;DR or Key Takeaways (if SEO-driven)
  • Introduction (hook + keyword)
  • Body sections (QAE, answer-first)
  • Conclusion (summary + CTA)
  • CTA copy options

Related Skills

  • article-page-generator: Page structure, schema, metadata, layout; content goes here
  • howto-section-generator: Dedicated HowTo step blocks (ordered steps, HowTo JSON-LD; vs FAQ)
  • copywriting: Frameworks (PAS, AIDA, BAB); headline formulas; short conversion copy
  • content-marketing: Article Orientations; content types
  • eeat-signals: E-E-A-T; author bio; citations; citations format
  • keyword-research: Keyword basis; search intent
  • competitor-research: Content gaps; structure to adopt; SERP audit for information gain
  • content-optimization: H2 keywords; Multimedia (tables, lists); keyword density
  • generative-engine-optimization: GEO strategy; AI citation

Frequently asked questions

What does the Article Content AI skill do?

When the user wants to write, generate, or create article body content—blog post body, long-form content, how-to guide, listicle. Also use when the user mentions "write article," "article content," "blog post content," "article body," "long-form content creation," "generate article," "article draft," "how-to guide content," "listicle content," "information gain," or "content density." For single post page structure, schema, and SEO metadata, use article-page-generator. For blog index/listing page, use blog-page-generator. For short ad, landing, or email copy, use copywriting.

Why use Article Content on TypingMind?

Because you install it once and use it with any model. Article Content is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Article Content in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kostja94/marketing-skills/tree/main/skills/content/article. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Article Content?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Article Content?

As many as you like. As long as a model supports skills, you can use Article Content with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Article Content AI skill free?

Yes. It is published on GitHub by kostja94 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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