# Article Summarizer > Deep-read any article, blog post, or web page and produce a structured expert analysis: concise summary, key bullet points, reader action items, and domain-adaptive expert commentary. Use this skill whenever the user shares a URL (Medium, Substack, dev.to, HN, any blog) or pastes article/post content and asks to "summarize", "analyse", "break down", "review", "read this", "what do you think of this", "give me the key points", "TL;DR this", or similar. Also trigger when the user drops a raw URL without any instruction — assume they want the full analysis. Works for any domain: engineering, product, finance, science, design, business, etc. - Skill: `anarefin/article-summarizer` (Agent Skill) - Install (CLI): `npx skillmds@latest add anarefin/article-summarizer` - Raw SKILL.md: https://api.skillmd.com/api/skills/anarefin/article-summarizer/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: anarefin (https://skillmd.com/u/anarefin) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/anarefin/article-summarizer --- # Article Lens Skill Produce a fast, deep, expert analysis of any article or web page. Target reading time for the output: **2–3 minutes** (shoot for this; 5 minutes is a hard ceiling — cut ruthlessly). --- ## Step 0 — Acquire the Content **If a URL is provided:** - Call `web_fetch` on the URL immediately. Do not ask the user to paste the text. - If `web_fetch` fails (paywalled, bot-blocked): tell the user briefly and ask them to paste the text. Do not stall. **If raw text is pasted:** - Use it directly. Do not call `web_fetch`. **If both URL and pasted text exist:** use the pasted text (it may already be the cleaned body). --- ## Step 1 — Domain Detection & User Confirmation (interactive) After acquiring content, infer the following **silently** (do not output this block): 1. **Author's apparent expertise level** — practitioner, academic, journalist, enthusiast 2. **Target audience the author wrote for** — beginner, intermediate, senior practitioner 3. **Content type** — opinion/essay, tutorial/how-to, news/announcement, research summary, case study, listicle Then infer **2–5 candidate domain labels** that best describe the article's subject matter. Think in terms of specific, meaningful domains — not vague categories. **Good domain label examples:** - Distributed Systems, Event-Driven Architecture, Consensus Algorithms - LLM Fine-tuning, Retrieval-Augmented Generation, AI Agents - SaaS Pricing Strategy, Product-Led Growth, Churn Analysis - Kubernetes Internals, eBPF, Platform Engineering - DeFi Protocols, Tokenomics, Smart Contract Security - Organizational Design, Engineering Management, Team Topologies **Then STOP and present the domain candidates to the user** using the `ask_user_input_v0` tool: - Question: "Which domain lens should I use for the Expert Lens? (pick one or more)" - Type: `multi_select` - Options: your 2–5 inferred domain labels + one fallback option: "General / Let Claude decide" - Include a brief one-line context before the tool call, e.g.: "I detected this article touches on a few domains — pick the lens(es) you want the Expert commentary to use:" **Wait for the user's selection before proceeding to Step 2.** Once the user responds: - Use the selected domain(s) to calibrate the Expert Lens persona and angle. - If multiple domains are selected, address each briefly in the Expert Lens (still max 2 paragraphs total — be tighter per domain). - If the user picks "General / Let Claude decide", use the primary inferred domain. - Do not re-state the user's selection back to them — just proceed directly to the output. --- ## Step 2 — Output Structure Render the following sections **in order**, in markdown, inline in chat. Use a horizontal rule (`---`) between sections. Keep the whole response tight. **Before the first section**, output a single metadata line: > 📖 **Reading time:** X min · *Article title or inferred topic* Calculate reading time from the source article word count at ~238 words/minute (average adult). Round to the nearest half-minute. Format: "3 min", "4.5 min", "7 min". Do not show the word count. --- ### 🧭 Summary *One tight paragraph. 4–6 sentences max.* - Lead with **what** the article argues or demonstrates — the core thesis. - Include the **so-what**: why this matters in context of the domain. - Note any significant **caveats or gaps** the author acknowledges. - Do NOT list bullet points here. Pure prose. --- ### 🔑 Key Points *5–9 bullets. Each bullet is 1–2 sentences — substantive, not paraphrased headers.* Rules: - Each bullet must carry information that would be **lost** if removed — no filler. - Preserve nuance: if the author made a qualified claim, preserve the qualification. - Order by importance, not by article order. - If the article is a listicle, distill and synthesize — do not echo the list. --- ### ⚡ Actions & Suggestions - 2–4 concrete, specific actions the reader should consider taking after reading this. - Calibrated to someone senior in the domain — skip "learn the basics" type suggestions. - Ground each action in something specific from the article. --- ### 🧠 Expert Lens *Adopt the persona of a seasoned expert in the **user-selected domain(s)**. One sharp, opinionated take — not a book report.* Pick **exactly one** of the following angles per selected domain (the most revealing for this article): - **Production/real-world gap**: What breaks down when this hits reality at scale? - **Unstated assumptions**: What must be true for this to hold? Are those assumptions safe? - **Trade-off glossed over**: What did the author sacrifice to make the argument clean? - **Dissenting position**: How would a credible expert who disagrees frame their objection? - **Historical context**: Has this been tried before? What actually happened? Write **1–2 paragraphs total** regardless of how many domains were selected. If multiple domains, weave them together or address each in a tight sentence or two — do not write separate blocks per domain. Dense, not padded. Cut if it isn't adding something the other sections missed. --- ## Formatting Rules - **No nested sub-bullets** — two levels max, and use second level sparingly. - Use `**bold**` for key terms or named concepts only — not for decoration. - No headers beyond the sections above (Reading time, Summary, Key Points, Actions, Expert Lens). - Do not add a preamble ("Here is my analysis of…") or a closing ("I hope this helps…"). - Do not re-state the user's domain selection or narrate the skill's internal process. - If the article is thin (< 400 words or a pure announcement), say so briefly before the summary and scale down Key Points to 3–5 bullets; skip the Expert Lens or note it's not warranted. --- ## Length Calibration | Content type | Target output length | |--------------------|----------------------| | Short post / essay | 350–500 words | | Standard article | 500–750 words | | Long-form / deep | 750–1000 words | | Research summary | 750–1000 words | Stay under 800 words for the full output in almost all cases. If you're going over, cut from Key Points and Expert Lens first — preserve the Actions section. --- ## Edge Cases - **Paywall / fetch failure**: Say "Couldn't fetch the page — paste the article text and I'll run the analysis." Nothing more. - **Non-article URL** (e.g., GitHub repo, docs page, landing page): Adapt gracefully. Note the content type at the top of Summary. - **Very technical paper** (arXiv, academic): Expert Lens should lean into methodology critique and replication concerns. - **Opinion/hot-take piece**: Weight the "Dissenting position" angle in Expert Lens. - **Multi-language content**: Respond in the same language as the user's message, not the article's language, unless the user asks otherwise.