Swathi 🌱 @idevnull
Just a stardust ✨ 土 (chi) Joined December 2014-
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@jianxliao @AnthropicAI @contextdotstore Built something similar OSS - github.com/townsquare-os/… Let me know what you think @jianxliao
Your codebase, but you can actually see it. I built a Claude Code skill: type /visualise <anything>; it reads your code, picks the right diagram, and opens it in your browser. Architecture, data flow, git branches, bundle size, correlations. One command. Zero deps👇
The Vishnu Sahasranama is 1000 names of Vishnu, chanted for centuries. On the page it looks like a flat list. It isn't. I built an atlas so you can wander it instead. sahasranama.github.io
The quiet surprise: 70 names recur, each time meaning something new. Pick one and gold threads connect it to its other lives. You can even play the recitation while you explore. Free and open.
Three lenses on the same thousand names: a Constellation that clusters them by theme of life, a Mandala that spirals them in chanting order, and the Litany itself, every name in Devanagari, grouped into its 107 ślokas.
Browse the live gallery, all interactive, all skill-generated: qlawd.github.io/visualise Inspired by @paraschopra's explainers + make-pages-interactive built the on-demand version as a Claude skill. Here's git-flow as an animated state machine 👇
Local-first. JSONL on disk. No DB, no cloud, no telemetry. Git-friendly. Apache 2.0. Alpha release, feedback welcome. github.com/lore-kb/lore
Ships as an MCP server. Install once. After that, Claude Code calls lore_capture / lore_search / lore_context as a side effect of normal conversation. You never type "lore" anything. Knowledge flows in automatically.
Every AI coding session generates knowledge. 99% of it is thrown away. I keep terminals open for a week because closing them loses a week of context. Built "lore" to fix it. Your knowledge base has a compiler. "pip install lore-kb"
LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating
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