/news-scanner

name: news-scanner
description: Surface the day's news events that actually moved a stock. For each notable headline across a watchlist (or the broader market), render a Bloomberg news tape / Benzinga Pro-style stream with sentiment, novelty, and the post-publish price reaction. Ranked by impact, capped at top N (default 15-20). The 6am sell-side morning-note prep workflow.

news-scanner

You hand over a watchlist and a time window. The skill pulls every news event Massive has on those tickers in the window, derives a sentiment score per ticker per article, measures whether the angle is novel or a re-run, computes the stock's price reaction since publish, ranks events by impact, and emits a stream of the top N.

This is the workflow a sell-side analyst runs at 6am to write the morning note. Twenty headlines that actually moved a stock, with the context (sentiment + novelty + reaction + volume anomaly + divergence flag) to write about them in 30 minutes. Unlike a news terminal or RSS reader, news-scanner ranks events by signal quality (price reaction × volume anomaly × novelty) rather than recency, and ships the methodology with the output.

When to invoke

• An analyst is prepping the morning note and wants the overnight tape

ranked by impact

• A PM is asking "what's the news on my book today"
• The user says "scan news on NVDA TSLA AAPL", "what moved overnight",

or "any catalyst on my watchlist"

• A trader wants to spot price/news divergence (negative headline,

positive reaction = bad news already priced in)

What you need

• A watchlist of tickers (default: NVDA, TSLA, AAPL, SPY, META, NFLX)
• A time window in hours (default: last 24h)
• `MASSIVE_API_KEY` exported in the environment
• Stocks Basic + Benzinga News add-on minimum

The skill runs at two fidelity tiers.

• **Tier A (Benzinga sentiment + minute aggs):** Benzinga News add-on

returns per-ticker `insights[]` with a categorical sentiment label ("positive" / "negative" / "neutral") and `sentiment_reasoning` from Benzinga's own NLP. Stocks Starter or higher gives reliable minute aggregates for the reaction window. This is the default tier.

• **Tier B (keyword fallback):** Benzinga News add-on missing or the

Benzinga `insights` field is empty. Sentiment falls back to a keyword scorer (positive: beat, raise, partnership, upgrade; negative: cut, miss, lawsuit, downgrade, recall, probe). Reaction calc still works on Stocks Basic but uses 5-minute aggregates instead of 1-minute. Documented in [`references/sentiment-scoring.md`](./references/sentiment-scoring.md).

What you get back

Two output layers from one analysis.

**Layer 1: canonical JSON** matching [`output-schema.json`](./output-schema.json). Per-event fields: ticker, published_at, source, headline, url, sentiment_score (in [-1, +1]), sentiment_source ("benzinga" or "keyword"), novelty_score, novelty_band, reaction_pct_since_publish, reaction_window_label, volume_anomaly_x, divergence_flag, context_line. UIs, alert pipelines, and downstream agents consume this.

**Layer 2: rendered stream** in Bloomberg news-tape / Benzinga Pro style. Three lines per event, optional `↳` continuation for context. Format rules in [`references/rendering.md`](./references/rendering.md). Compact, scanable, key:value pairs. Claude Code users read this.

How it works

1. For each ticker in the watchlist, pull `/v2/reference/news?ticker={t}&published_utc.gte={window_start}&limit=50`. Dedupe by `article_url` across the merged set so a story syndicated across publishers only appears once. See [`references/news-sources-and-coverage.md`](./references/news-sources-and-coverage.md). 2. Score sentiment per (ticker, article). Prefer the Benzinga `insights` entry for that ticker if present (map "positive" → +0.7, "neutral" → 0, "negative" → -0.7); otherwise fall back to a keyword scorer over the title and description. See [`references/sentiment-scoring.md`](./references/sentiment-scoring.md). 3. Score novelty per (ticker, article). Bucket the last 7 days of articles for the ticker; compute TF-IDF over titles + first-sentence of description; cosine distance to nearest neighbor in the bucket. Distance > 0.6 = high novelty (new angle), 0.3-0.6 = medium, < 0.3 = low (already covered). See [`references/novelty-detection.md`](./references/novelty-detection.md). 4. Compute the price reaction. Pull `/v2/aggs/ticker/{ticker}/range/5/minute/...` from publish minute through min(publish + 60 minutes, market close). Reaction % = (close at window end / close at publish minute) - 1. Volume anomaly = avg per-minute volume during the window / prior-5-day same-time-of-day average per-minute volume. 5. Flag price/news divergence per [`references/price-news-divergence.md`](./references/price-news-divergence.md): positive sentiment + negative reaction = priced in / sell-the-news; negative sentiment + positive reaction = bad news already priced in. 6. Rank by `impact = |reaction_pct| × volume_anomaly × novelty_score`. See [`references/impact-ranking.md`](./references/impact-ranking.md). Emit top N (default 15).

Foundations used

• [`massive-api-patterns`](../massive-api-patterns) for REST auth, the

best-price fallback chain for spot, and rate-limit handling on the per-ticker news fan-out

Output mode: stream

Stream mode is the format Bloomberg's news tape, Benzinga Pro's feed, and Reuters Eikon use for incoming events. Each event is a self-contained block; the reader scans top to bottom and stops when they see one they want to act on. Inherited from [`options-flow/references/rendering.md`](../options-flow/references/rendering.md), adapted for news per [`references/rendering.md`](./references/rendering.md).

Endpoints used

• `GET /v2/reference/news?ticker={t}&published_utc.gte={iso}&limit=50`:

Benzinga News. Returns `results[]` with `id`, `title`, `description`, `published_utc`, `article_url`, `tickers