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Article Writing

Community
ericrisco
article-writing

Use when writing one long-form article end to end — answer-first lede, question-shaped headings, plus its on-page surface (title, meta, slug, FAQ, Article/FAQPage JSON-LD) — or fixing a draft that buries the answer or reads AI-padded. NOT keyword research or topic selection (that is `seo-geo`), NOT the editorial calendar (that is `content-engine`).

Overview

Publisherericrisco
Repositoryrsc-harness
Skill namearticle-writing
Stars
239
Forks
24
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Article Writing 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.
    https://github.com/ericrisco/rsc-harness/tree/main/skills/article-writing
  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/ericrisco/rsc-harness.git /tmp/rsc-harness
mkdir -p .claude/skills
cp -r /tmp/rsc-harness/skills/article-writing .claude/skills/article-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Article Writing 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 Writing 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 Writing 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.

Article writing

Draft one long-form article end to end: the prose and the on-page surface that ships with it — answer-first lede, question-shaped headings, title tag, meta description, slug, FAQ block, and the JSON-LD that makes the piece machine-readable.

You own a single finished article. You do not pick the topic, build the calendar, or define the house voice — those are siblings below.

When NOT to use

You want…Go to
Keyword research, SERP tracking, technical SEO, deciding which topics to target../seo-geo/SKILL.md
Editorial calendar, topic-cluster plan, pipeline across many pieces../content-engine/SKILL.md
The reusable brand tone-of-voice spec the article is written in../brand-voice/SKILL.md
A conversion landing or sales page (hero, offer, CTA)../landing-copy/SKILL.md
An email newsletter issue (subject line, send)../newsletter/SKILL.md
Product docs, API reference, software how-tos../technical-writing/SKILL.md
A customer outcome story / narrative../case-studies/SKILL.md

Rule: if the deliverable is not one publishable article, you are in the wrong skill.

Start from intent, not a word count

Before you write a sentence, read the top of the SERP for the target query. Name two things: the dominant intent (informational, transactional, comparison, navigational) and the winning format Google already rewards (listicle, step guide, definition + table, comparison). Match that format — fighting the shape Google already chose loses.

Then set depth from intent, not from a number you were handed. The first-page Google average is ~1,447 words across 11.8M results (Backlinko) — a descriptive average, never a target. Thoroughness and intent satisfaction rank, not length.

IntentTypical depthShape
Simple how-to / quick answer400–800 wordsDirect answer, short steps, one image
Standard informational post1,500–2,000 wordsAnswer-first lede + question H2s
Comprehensive guide1,700–2,500 wordsFull subtopic coverage, tables, FAQ
Pillar page2,500–5,000 wordsHub with two-way cluster links

Why: padding a 600-word answer to 2,000 to "look thorough" dilutes it and reads as filler. Cutting a guide to 800 words leaves the query half-answered. Length follows the question.

The answer-first lede

The first ~200 words must directly and completely answer the primary query. Lead with the answer (TL;DR-first / inverted pyramid), then expand. This is the structure that wins featured snippets and AI Overview citations — and with zero-click hitting ~60% of searches (2024) and AI Overviews appearing in ~13% of queries (May 2025), being the extracted answer matters more than the click.

markdown
<!-- Bad: warms up for three paragraphs before answering -->
## Should you compost in an apartment?
Composting has become increasingly popular in recent years as more people
look for sustainable lifestyle choices. Many city dwellers assume they can't
participate because of limited space. But is that really true? Let's explore
the fascinating world of urban composting and find out together.
markdown
<!-- Good: answers in the first two sentences, then expands -->
## Can you compost in an apartment?
Yes — a sealed countertop bokashi bin or a small worm bin (vermicomposting)
lets you compost food scraps in a flat with no yard and no smell. Bokashi
ferments scraps in ~2 weeks; a worm bin yields finished compost in 3–6 months.
Here is how to choose between them and set one up in a 60×40 cm footprint.

If the query is a question, the H1 or first H2 should be that question and the next sentence should answer it. Worked lede examples are in references/on-page-seo.md.

Outline as a question map

Build the skeleton from real subtopics, not from what you feel like writing.

  • One H1, matching the primary query or its close paraphrase.
  • H2/H3 are questions or named subtopics that mirror the SERP's "People also ask", related searches, and the headings competitors share — plus the gaps they all miss (that gap is your edge).
  • One idea per heading. A heading that needs an "and" is two headings.
  • Headings are subtopics, not slogans: ## How much does a standing desk cost? not ## The Price Question.

Why question-shaped headings: only ~38% of pages cited in AI Overviews rank top-10, so clean, extractable, question→answer structure can win citations without traditional authority. Make every section answerable on its own.

Drafting for depth and E-E-A-T

Google does not penalize AI-assisted content as such. It penalizes scaled content abuse — high-volume, no-editorial-review, thin, no-first-hand-experience pages. The March 2026 core update named scaled content abuse a primary target; offending sites saw 50–80% traffic drops. The defense is not avoiding AI; it is genuine value, depth, and human review.

So every draft earns its keep with E-E-A-T (Experience, Expertise, Authoritativeness, Trust — Trust is the load-bearing member):

  • First-hand experience — a thing you tested, measured, or saw. "We ran the worm bin for 90 days and weighed the output" beats "worm bins are effective".
  • Original data or insight — a number, comparison, or angle not already on page one.
  • Credible cited sources for claims you did not generate yourself — link them inline.
  • Clear authorship — a named author with relevant standing, not "admin".
  • Match intent over keyword density. Answer the question fully; the keywords fall out naturally. Never stuff.

Run a human-review pass before ship. If nothing in the draft could only have been written by someone who actually knows the topic, it is thin — add experience or do not publish.

The on-page surface

Every article ships with these. Keep them in the file's front-matter or a clearly labelled block so scripts/verify.sh can lint them.

  • Title tag: 50–60 characters / under ~580–600 px desktop (~480 px mobile). Put the primary keyword in the first ~30–35 characters. Titles of 51–55 chars are rewritten by Google least often.
  • Meta description: 140–160 characters (desktop ~920 px ≈ 158 chars; mobile cuts at ~120). One to three sentences, lead with the value. It does not rank, but it drives CTR and is often the snippet AI engines echo.
  • H1: exactly one, matching the query.
  • Slug: short, lowercase, hyphenated, keyword-bearing, no stop-word noise — /compost-in-apartment not /how-to-start-composting-in-your-apartment-today.
  • FAQ block: 3–6 real questions from "People also ask", each answered in 2–4 sentences.

Full pixel/char tables, slug rules, and copy-ready Article/BlogPosting + FAQPage JSON-LD (JSON-LD only — never microdata) live in references/on-page-seo.md. The JSON-LD must describe what is actually on the page; schema that does not match visible content is a quality flag, not a win.

Internal links and topical authority

Place 3–5 contextual internal links in the body of a standard article (more only for a long-form pillar). Rules:

  • Descriptive anchor text — worm bin setup guide, never click here or a bare URL.
  • Keep priority pages within ~3 clicks of the post.
  • For a pillar, link two ways: pillar → each cluster article and each cluster article → pillar. That two-way map is the topical-authority signal AI engines read.

You insert the link slots and anchors that fit this article. Deciding the cluster structure — which pillar owns which clusters across the site — is ../content-engine/SKILL.md's job, not yours.

Cut the AI tells and the fluff

Do one ruthless pass: delete every sentence that adds no fact. If a sentence could sit in any article on any topic, it is filler.

Banned on sight (short sample): "In today's fast-paced world", "It's important to note that", "When it comes to", "Let's dive in", "the world of X", "navigating the landscape of", "unlock the power of", "in conclusion". The full banlist with Bad→Good rewrites and the depth self-review is in references/ai-tell-banlist.md — and that file is the single source verify.sh greps against.

markdown
<!-- Bad: 28 words, zero facts -->
In today's fast-paced world, it's important to note that choosing the right
standing desk can really make a difference when it comes to your health.
markdown
<!-- Good: 19 words, three facts -->
A standing desk adjustable from 70–120 cm fits users 1.5–2.0 m tall and cuts
the lower-back load reported across sit-all-day workdays.

Anti-patterns

Anti-patternWhy it failsDo instead
Padding to hit a word countDilutes the answer; reads as fillerSet depth from intent; ~1,447w is an average, not a target
Intro that warms up before answeringLoses snippets, AI Overviews, and ~60% zero-click readersAnswer the query in the first ~200 words
Keyword stuffing for densityReads spammy; Google rewards intent match, not densityAnswer fully; keywords fall out naturally
H2s that are slogans, not subtopicsNot extractable; misses People-also-ask citationsQuestion-shaped, one idea per heading
No named author or cited sourcesThin E-E-A-T; vulnerable in core updatesAdd first-hand experience, data, citations, an author
FAQ with no FAQPage schema (or schema ≠ visible content)Not machine-readable; mismatched schema is a quality flagShip matching FAQPage JSON-LD describing on-page Q&As
Generic AI-tell proseFlagged as scaled, low-value contentRun the banlist + delete-no-fact-sentence pass
Ignoring the SERP's winning formatFights the shape Google already rewardsMatch the dominant format, then beat it on depth

Ship checklist

Restating the gates verify.sh enforces, for the human review:

  • Answer-first lede — primary query fully answered in first ~200 words
  • Exactly one H1; at least two question-shaped H2s
  • Title 50–60 chars (keyword early); meta 140–160 chars
  • JSON-LD present with @type Article/BlogPosting; FAQPage too if an FAQ section exists
  • At least one contextual internal-link slot with a descriptive anchor (target 3–5)
  • AI-tell / fluff banlist scan is clean
  • Depth matches intent; first-hand experience or original data present; author + sources named

Run scripts/verify.sh path/to/article.md. It is a lint of structure and banned phrasing — it does not judge whether the content is good. That is the capability eval's job, and yours.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Article Writing AI skill do?

Use when writing one long-form article end to end — answer-first lede, question-shaped headings, plus its on-page surface (title, meta, slug, FAQ, Article/FAQPage JSON-LD) — or fixing a draft that buries the answer or reads AI-padded. NOT keyword research or topic selection (that is `seo-geo`), NOT the editorial calendar (that is `content-engine`).

Why use Article Writing on TypingMind?

Because you install it once and use it with any model. Article Writing 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 Writing in TypingMind?

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

Which AI models can use Article Writing?

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 Writing?

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

Is the Article Writing AI skill free?

Yes. It is published on GitHub by ericrisco 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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