Built a broadcast dashboard monitoring AI agent developments across 21 primary sources - here's what I'm tracking and what's missing

Agent-related developments are some of the hardest signals to track right now - they're spread across arXiv papers, GitHub repos, model release notes, incident reports, and policy documents simultaneously. I've been running a pipeline that pulls from arXiv (cs.AI/cs.LG/cs.CL), Hugging Face daily papers, Semantic Scholar, GitHub Trending, the AI Incident Database, GovAI, CSET, and a handful of others. Stories that cluster around agents - tool use, function calling, multi-agent frameworks, reasoning benchmarks - tend to surface well because they hit multiple sources at once. What the system is weak on for this community: \- Agent benchmarks specifically (mostly caught when a paper drops on arXiv, but benchmark leaderboard churn is invisible) \- Open-source framework releases that don't trend on GitHub or hit a paper \- Real deployment incidents from practitioners (AIID captures formal reports, not community anecdotes) Genuinely curious what sources are actually followed in here to stay current on the agent space. I'll drop the dashboard link in the comments per the sub rules.