last30days

Multi-source research across Reddit, X, YouTube, Hacker News, Polymarket, and the web surfaces what communities are discussing now. It filters results to the last 30 days and weights signals like engagement and recency to synthesize cross-source findings into a compact report.

Yes, cross-source synthesis of recent findings produces a copy-paste-ready prompt pack and a reusable context snippet. These outputs are formatted for immediate deployment into AI agents like Claude Code or Codex.

Engagement-weighted scoring analyzes upvotes and shares across Hacker News, Polymarket, and other sources from the last 30 days. It de-duplicates results and links related findings to surface highly valued community discussions.

The pipeline operates deterministically with date filtering and deduplication without requiring external dependencies. Optional WebSearch integration can be added to expand web coverage during the research process.

Running a deterministic pipeline with date filtering to the last 30 days automates trend monitoring effectively. It returns a structured report alongside a reusable context snippet suitable for integration with AI agents.

Deterministic date filtering strictly limits results to the last 30 days, while built-in deduplication removes repeated findings across sources. This ensures the synthesized report contains only recent, unique, and engagement-weighted data.