hada-scout

3-phase in-session pipeline that monitors hada.io (via feedburner RSS) for relevant articles, uses a haiku LLM batch to pre-score relevance, and dispatches full /scout analysis only on high-scoring candidates.

Purpose

Replace the v1.0 keyword-regex approach with context-aware LLM pre-scoring. Haiku evaluates all feed titles in a single batch call, reducing false positives from ~30-40% to ~5-10% and eliminating the external CronJob dependency for user-invoked runs.

Architecture: 3-Phase In-Session Pipeline

Phase 1 — Fetch & Parse

1. WebFetch the hada.io RSS feed (https://feeds.feedburner.com/geeknews-feed)
2. Parse all items: title, URL, publication date
3. Default: latest 50 items (configurable via --limit or HADA_SCOUT_LIMIT)