Data infrastructure for AI agents
Fewer tokens, More context
Attention0 transforms important public information into clean, structured, agent-ready data with historical time series, so agents retain the context that raw pages and one-time snapshots miss.
Installation
$ npx skills add https://github.com/socialnetwork0/attention0-skills --skill attention0token savings + historical context
$ curl https://www.youtube.com/@mrbeast
tokens[live raw page, scripts, styles, tracking payloads]
raw: https://www.youtube.com/@mrbeast
clean profile, latest metrics, historical signals
3 platforms live. More coming soon.
Live data sources are accessible at attention0.com/{platform}/{handle}.md
/youtube/@mrbeast.md/tiktok/@charlidamelio.md/ranks/vercel.com.mdComing soonComing soonComing soonComing soonHow it works
Three steps from raw web to agent-ready context.
Our workers monitor YouTube, TikTok, domain rankings, and more platforms every 24 hours — building time-series snapshots of profiles, stats, content metadata, and engagement trends.
Raw HTML and API responses are parsed, normalized, and structured. No noise, no duplicates — just the signal your agent needs.
Clean data lands in a plain .md file at a predictable URL. Fetch it with curl, include it in a prompt, or pipe it into your RAG pipeline.
Power your next agent
Start fetching curated social and developer signals in minutes. No setup, no API keys, no rate limit headaches.