scout-sourceslisted

# scout-sources Answers "what video should we clip next?" deterministically instead of by vibes. Professional clip channels hunt **outliers** — videos performing far above their channel's baseline. The cheap keyless proxies, all available from yt-dlp: - **velocity** `2 * log10(1 + views/day)` — reach × freshness - **outlier** `min(10, views/subscribers)` — 3x+ is real signal, 5–10x is strong - **engagement** `min(5, comments per 1k views)` — talked-about-ness - **peaky** `min(3, 10 * stdev(replay heatmap))` — a spiky most-replayed graph means the video CONTAINS clippable moments; flat means evenly mediocre - **curiosity** `min(1.5, question/superlative framing in the title)` — sources whose own title is a curiosity hook ("how come…", "richest woman ever") yield the cold-open question moments the pipeline now leads with `score = velocity + outlier + engagement + peaky + curiosity` (see `score.py`). ## Invoke ``` .claude/skills/scout-sources/scout-sources.sh [out.json] [query ...] ``` - `out.json` (optional): default `work/_scout/candidates.json` - `query ...` (optional): seed searches; default reads `niches.txt` (channel analytics — humor pods + productivity/AI — plus visually-rich, question-driven niches: space, wealth, true-crime, nature, history) Env knobs: `SCOUT_PER_QUERY` (12 results/query), `SCOUT_SHORTLIST` (20 full fetches), `SCOUT_MIN_VIEWS` (100000), `SCOUT_DUR_MIN`/`SCOUT_DUR_MAX` (900/10800s — long-form only). ## Output `candidates.json` with ra