technical-article-writer — Claude Code skill: how to install

---
name: technical-article-writer
description: "Write technical articles and blog posts for developer audiences — tutorials, explainers, benchmarks, bug hunts, postmortems, and 'we rewrote it in X' posts — with title variants and developer-grade article structure. Use whenever the user asks to write a blog post, technical article, dev.to or Medium post, or any long-form technical content, including 'write about [technical topic]', 'turn this into a blog post', or 'I want to publish something about X', even without naming a format. Do NOT use for newsletter or Substack issues — use samber/cc-skills@substack-ghostwriting instead. Do NOT use for codifying an author's voice — use samber/cc-skills@copywriting-prose-creator instead."
user-invocable: true
license: MIT
compatibility: Designed for Claude or similar AI agents.
metadata:
  author: samber
  version: "1.3.2"
  openclaw:
    emoji: "📝"
    homepage: https://github.com/samber/cc-skills
allowed-tools: Read Edit Write Glob Grep Agent WebFetch WebSearch AskUserQuestion
---

**Questions:** Ask the user through the environment's question tool — never as plain-text prose. One question at a time, 2–4 tappable options, wait for the answer. If the environment has no question tool, ask in prose with the same options, one at a time.

# Technical Article Writer

Write technical articles that developers actually want to read. This skill combines structural frameworks from technical writing, hook engineering from copywriting, and practitioner-tested patterns for developer content.

## Core philosophy

Most technical articles fail because of structural problems, not bad ideas: burying the lede, mixing content types, weak openings, no clear motivation, or trying to cover too much.

Developer audiences have a built-in BS detector. The best technical content leads with specificity and honesty. It sounds like a smart colleague explaining something interesting, not a marketer pitching. Acknowledge your expertise level, solve a specific problem, use real examples.

Not for reference documentation aimed at non-native readers or machine translation (→ See `samber/cc-skills@humanizer-en-asd-ste100` skill for ASD-STE100 Simplified Technical English).

---

## Workflow

Follow these phases in order. Each phase produces a concrete artifact the user reviews before moving on. **Phase 1 is mandatory — always ask the user the intake questions and wait for answers before writing anything.** If the user already provided some context, extract what you can and ask only about missing pieces.

### Phase 1: Idea sharpening (interview)

**Stop and ask.** Before writing anything, present the intake questions below to the user and wait for their answers. Do not skip this phase, do not infer silently, and do not start drafting until you have explicit answers or confirmation on every item. Ask the user (or extract from context and confirm):

1. **Topic**: What specific thing are you writing about?
2. **Objective**: What's the primary goal of this article? Present these options through the question tool (push back if the user picks more than one — a single primary CTA converts far better than competing asks):
   - Newsletter subscription / audience growth
   - Personal branding / thought leadership / authority in a niche
   - Product or service signup / free trial
   - Direct purchase
   - Lead generation (download, gated asset, whitepaper)
   - Demo or sales call booking
   - Community join (Discord, Slack, forum)
   - Engagement (reply, share, comment, restack)
   - Reader support (paid subscription, tip, sponsorship)
   - No conversion goal (purely informational / educational)

   The objective shapes the CTA, how much you give away vs. tease, and where conversion points sit. It will be passed directly to the `copywriting-cta` skill in Phase 5b.

3. **Audience**: Who reads this? (junior devs, senior engineers, CTOs, general tech, DBA, frontend developer...)
4. **Content type**: Which pattern fits? (see `references/article-structures.md` for full templates)
   - The Bug Hunt / We Rewrote It in X / How We Built It / Lessons Learned
   - Thoughts on Trends / Benchmark / Tutorial / Explainer
5. **Length target**: Short (800-1200), Medium (1500-2500), Long (3000+)
6. **One-sentence thesis**: The single claim or takeaway. If the user can't state this, help them.

If the user already provided most of this, extract from conversation and confirm. But if critical pieces are missing, **stop and ask before proceeding**. Don't guess at the audience, content type, or thesis. A wrong assumption here wastes an entire draft.

Specifically:

- If the topic is vague ("write about Java performance"), ask what specific aspect and what the reader should walk away knowing.
- If the audience is unclear, ask. A post for junior devs has a completely different structure than one for senior engineers.
- If you can't infer a thesis, ask the user: "What's the one thing you want the reader to remember?" If they can't answer, help them find it through questions about what surprised them, what they'd tell a colleague, or what they wish they'd known earlier.
- If the content type is ambiguous (could be a tutorial or an explainer), ask which experience the reader should have: following along hands-on, or building a mental model.

Only proceed to Phase 2 once you have enough clarity on topic, audience, content type, and thesis to write a coherent outline. It's cheaper to ask one question now than to rewrite 2000 words later.

**Idea quality filters.** Apply these before investing in a draft:

Julia Evans's heuristic: the best technical content comes from what you struggled with, not what you mastered. If the topic feels too "textbook", push toward the specific struggle, surprise, or counterintuitive finding.

Julian Shapiro's novelty filter. The idea should fit at least one:

- **Counter-intuitive**: "I never realized the world worked that way"
- **Counter-narrative**: "That's not how I was told it worked"
- **Shock and awe**: "I had no idea that was possible"
- **Elegant articulation**: "I always felt that way but couldn't put it into words"
- **Makes you feel seen**: "Finally someone gets my experience"

If the idea doesn't pass any filter, say so. Help the user find the angle that does.

### Phase 2: Title generation

Generate **10 title variants** using different hook strategies. Read `references/hooks-and-titles.md` for the full framework of 10 hook types and headline formulas.

Constraints for developer audiences:

- 7-12 words optimal for LinkedIn/B2B sharing
- Specificity over cleverness ("How to profile Go allocations with pprof" > "Mastering Go Performance")
- Numbers and data signal rigor
- Avoid superlatives ("ultimate", "complete", "everything you need")
- Technical keywords attract the right audience
- Cognitive dissonance creates curiosity without clickbait

Present 10 titles ranked by assessment, with a brief note on why each works. Let the user pick or remix.

### Phase 3: Hook and intro

**Delegate the hook to the `copywriting-hooks` skill.** Pass the topic, audience, language, content type, and length target from Phase 1. The skill will propose 3-4 hook options (2 candidates each) and wait for the user to pick. Do not write the hook yourself — let the skill run its full workflow.

After the user picks a hook, write the remaining intro (2-3 paragraphs) around it:

1. **Hook** (chosen by the user via `copywriting-hooks`)
2. **Stakes** (1-2 sentences): Why should the reader care? What's the cost of not knowing this?
3. **Promise** (1 sentence): What will the reader gain by the end?

Address three reader objections:

- **Untrustworthy**: Why should I listen to you? (credibility hook or specific experience)
- **Irrelevant**: Why does this matter to me? (stakes)
- **Implausible**: Will this actually deliver? (promise + specificity)

Anti-patterns to avoid:

- Starting with a dictionary definition
- "In today's fast-paced world..."
- "Have you ever wondered..."
- Burying the interesting part after 3 paragraphs of context
- Explaining what the article will cover instead of demonstrating value

### Phase 4: Body structure

Choose structure based on content type. Read `references/article-structures.md` for detailed templates per content type.

General structural principles:

- **One idea per section.** If a section does two things, split it.
- **Show, then tell.** Lead with the example, code snippet, or observation. Then explain.
- **Progressive disclosure.** Start with the simplest version, then add complexity.
- **Every section earns the next.** Each section should create enough momentum to pull the reader forward. If a section could be skipped, cut it.

For code-heavy articles:

- Snippets < 20 lines, focused on one concept
- Always show "before" (problem) and "after" (solution)
- Annotate non-obvious lines
- Link to repo for full code, show only the interesting parts inline

For opinion/analysis:

- Steelman the opposing view before arguing against it
- Concrete examples, not abstract reasoning
- Quantify claims ("2x faster" not "much faster")

### Phase 5: Draft the full article

Write the complete article. Interleave hook, body sections, and conclusion.

For the **conclusion**, avoid restating the article. Instead pick one of:

- **Implication**: What does this mean for the reader's work going forward?
- **Open question**: What's still unresolved or worth exploring?
- **Call to action**: What should the reader do next?

### Phase 5b: CTA

**Delegate to the `copywriting-cta` skill.** Pass the objective from Phase 1 as the primary objective. The skill will interview the user for any missing inputs (article context, audience relationship, funnel stage, mechanism) and produce the complete CTA recommendation — copy, form, mechanism, A/B test plan, and accessibility check.

Place the CTA output at the end of the article, after the conclusion. Do not write a CTA yourself.

### Phase 5c: Humanize

Invoke a humanizer skill (e.g. "humanize", "humanizer", "de-slop", "natural writing check", "AI detection cleanup", "rewrite like a human") to strip AI-generated patterns — filler words, predictable cadence, over-hedging, hollow transitions, inflated language. Developer audiences have a built-in BS detector; AI-sounding prose kills trust before the reader reaches the technical content.

**Preserve the hook and title.** The opening hook (Phase 3) and title (Phase 2) were deliberately engineered for curiosity and credibility. Instruct the humanizer to leave them intact — rewriting them for "naturalness" destroys the copywriting structure that earns the click and the first scroll.

### Phase 6: Image suggestions

After the draft is complete, suggest **1-3 images** with specific placement in the article. For each image, provide:

- **Placement**: Where in the article (e.g. "as the hero/cover image", "after the intro", "between section X and Y")
- **Purpose**: What the image adds (break up a long text section, illustrate a concept, set the tone, visualize data)
- **Description**: What the image should depict

Offer to generate a **Midjourney prompt** for each suggested image. If the user accepts, use the latest Midjourney model conventions to write the prompt.

- Use `--ar 16:9` or `--ar 3:1` for hero/cover images and wide illustrations (optimal for article headers), `--ar 3:2` for smaller inline images.
- Refer to up-to-date Midjourney documentation for current prompt syntax and parameters.

### Phase 7: Title finalization

Revisit titles from Phase 2. Now that the full piece exists, some titles fit better. Present top 3 with a recommendation.

---

## Output format

Present the article in clean markdown with:

- The chosen title as H1
- A subtitle or meta-description (1 sentence)
- The full article body
- Image suggestions with placement notes (and Midjourney prompts if accepted)
- A "Title alternatives" section at the end with 2-3 runner-up titles
- A social teaser (only if the user accepted — offer after the draft, don't auto-generate)

---

## Reference files

Read these when the corresponding phase needs more depth:

- `references/hooks-and-titles.md` -- The 10 hook types, 6 copywriting frameworks (PAS, AIDA, BAB, FAB, PASTOR, 4Us), headline formulas, and research data. Read during Phase 2 and Phase 3.
- `references/article-structures.md` -- Detailed templates for each of the 8 content types, Diataxis framework, structural anti-patterns, and transition techniques. Read during Phase 4.