[OC] 907 AI agent skills projected into a 3D latent space (MiniLM embeddings + UMAP, clusters labeled by a local 2B LLM) Visualization

What This Visualization Shows

This data visualization displays "[OC] 907 AI agent skills projected into a 3D latent space (MiniLM embeddings + UMAP, clusters labeled by a local 2B LLM)" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on **Data source:** [VoltAgent/awesome-agent-skills](https://github.com/VoltAgent/awesome-agent-skills) — a public, curated list of \~900 agent skills from Anthropic, Microsoft, Stripe, Figma, Sentry, and 156 other GitHub orgs.

**Tools:** Python · sentence-transformers (`all-MiniLM-L6-v2`) · umap-learn · scikit-learn KMeans · Ollama + `gemma4:e2b` for cluster labels · Three.js for the 3D render.

**What you're seeing:** each point is one skill. Skills with similar descriptions end up near each other, so you can watch how the agent-skills ecosystem self-organizes — Sentry debugging, Flutter mobile, Azure AI, auth, marketing, and Figma-to-code all carve out visibly distinct regions.

**Pipeline:**

* Parse the README's \~900 one-liners into `(name, team, description)` * Embed `name: description` with MiniLM (384-d) * Reduce to 3D with UMAP (cosine) * Cluster in the 384-d space with KMeans(k=10) — *not* on the 3D projection; projection is lossy * Label each cluster by asking Gemma 4 (running locally via Ollama) for a 3–6 word human title over its 30 centroid-nearest members * Render with Three.js (glow sprites, nearest-neighbor edges, orbit controls)

**Interactive:** color by topic or by authoring team (161 orgs), search across name/description/team, click any point for the full skill entry.

Live: [https://shmulc8.github.io/agent-skills-network/](https://shmulc8.github.io/agent-skills-network/) Code + pipeline: [https://github.com/shmulc8/agent-skills-network](https://github.com/shmulc8/agent-skills-network)

Looking to run this at much bigger scale on a larger skills dataset soon — if you know of curated collections beyond this one, I'd love pointers., which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

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Data Analysis and Insights

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