I kept procrastinating on taking notes from articles I read. The cycle was always the same: read something interesting, tell myself I'll write proper notes later, never do it. So I built a tool to do it automatically. Paste any article → Claude AI extracts the key concepts → you get 3–7 atomic Markdown notes, ready to drag into Obsidian. Try it: https://qonspekt.github.io/qonspekt/ Each note gets: YAML frontmatter (title, tags, aliases) [[wikilinks]] connecting related concepts from the same article ## Sources section with the original URL Proper filename (concept-slug.md) The whole thing is one HTML file. No framework, no build step, no server. const response = await fetch('https://api.anthropic.com/v1/messages', { method: 'POST', headers: { 'Content-Type': 'application/json', 'x-api-key': userApiKey, 'anthropic-version': '2023-06-01', 'anthropic-dangerous-direct-browser-access': 'true', // official BYOK header }, body: JSON.stringify({ model, max_tokens: 4096, system, messages }) }); The anthropic-dangerous-direct-browser-access: true header is Anthropic's official way to support BYOK browser tools. Your key goes from your browser directly to Anthropic — I have no server to log anything. The trickiest part: Claude sometimes wraps output in markdown code fences even when told not to. const raw = data.content?.[0]?.text || ''; const match = raw.match(/\[[\s\S]*\]/); // extract JSON array regardless of wrapping if (!match) throw new Error('Could not parse response'); const notes = JSON.parse(match[0]); This regex approach handles both clean JSON and fenced output reliably. After generating, there's a "Share" button that base64-encodes all notes into the URL hash: const enc = btoa(unescape(encodeURIComponent(JSON.stringify(notes)))); const url = location.origin + location.pathname + '#shared=' + enc; navigator.clipboard.writeText(url); On load, if the hash starts with #shared=, it decodes and renders the notes in read-only mode. No server, no database, no account needed for the recipient. Getting the right structure took iteration. Key constraints that worked: - Extract 3-7 key concepts, write one atomic note per concept - Each note is self-contained but uses [[wikilinks]] to reference related concepts from the same batch - 150-280 words per note body - Tags: 2-4, lowercase, hyphens for spaces - Return ONLY a valid JSON array, no markdown fences The "same batch" constraint for wikilinks is important — it makes the notes interconnected without hallucinating links to notes that don't exist. ~$0.003 per article with Claude Haiku 4.5. New Anthropic accounts get free credits. MIT licensed: https://github.com/Qonspekt/qonspekt Would love feedback on the note structure or the prompt. What frontmatter fields do you typically use in your vault?