phase-2: extract shared utils

server/analyst/CatalystAnalyst.js

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+import { YahooClient } from '../market/YahooClient.js';
+
+const NEWS_QUERIES = ['stock market today', 'earnings report', 'market news'];
+const MAX_STORIES = 15;
+const TICKER_REGEX = /^[A-Z]{1,6}$/;
+
+export class CatalystAnalyst {
+  constructor({ logger } = {}) {
+    this.client = new YahooClient();
+    this.logger = logger ?? { write: (msg) => process.stdout.write(msg) };
+  }
+
+  async run() {
+    this.logger.write('🔍 Fetching market news...');
+    const stories = await this._fetchNews();
+    const tickers = this._extractTickers(stories);
+    this.logger.write(` ${stories.length} stories, ${tickers.length} tickers\n`);
+    return { tickers, stories };
+  }
+
+  async _fetchNews() {
+    const seen = new Map();
+    for (const query of NEWS_QUERIES) {
+      try {
+        const { news = [] } = await this.client.yf.search(query, { newsCount: 8, quotesCount: 0 });
+        for (const s of news) {
+          if (!seen.has(s.title)) {
+            seen.set(s.title, {
+              title: s.title,
+              publisher: s.publisher,
+              link: s.link,
+              relatedTickers: s.relatedTickers ?? [],
+            });
+          }
+        }
+      } catch {
+        /* skip failed query */
+      }
+    }
+    return [...seen.values()].slice(0, MAX_STORIES);
+  }
+
+  _extractTickers(stories) {
+    const tickers = new Set();
+    for (const { relatedTickers } of stories) {
+      for (const t of relatedTickers) {
+        const clean = t.split(':')[0].toUpperCase();
+        if (TICKER_REGEX.test(clean)) tickers.add(clean);
+      }
+    }
+    return [...tickers];
+  }
+}

server/analyst/LLMAnalyst.js

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+import Anthropic from '@anthropic-ai/sdk';
+
+// LLMAnalyst — uses Claude Haiku to analyze news catalyst stories.
+//
+// Given a list of news headlines and the tickers already identified,
+// it produces:
+//   - A concise market summary (2-3 sentences)
+//   - Industries likely to be affected (beyond the directly mentioned tickers)
+//   - Up to 5 related tickers worth watching
+//   - A risk sentiment assessment (BULLISH / NEUTRAL / BEARISH)
+//
+// Requires ANTHROPIC_API_KEY in environment.
+
+const SYSTEM_PROMPT = `You are a professional equity analyst. You will be given a list of today's market news headlines and the tickers already identified as catalysts.
+
+Your job is to:
+1. Write a 2-3 sentence market summary capturing the dominant theme
+2. Identify up to 4 industries that are likely to be secondarily affected (not directly mentioned but impacted by contagion, supply chain, regulation, or macro effects)
+3. Suggest up to 5 related ticker symbols worth screening that are NOT already in the provided list
+4. Assess overall market sentiment as BULLISH, NEUTRAL, or BEARISH based on the news
+
+Return ONLY valid JSON in this exact shape — no markdown, no explanation:
+{
+  "summary": "string",
+  "sentiment": "BULLISH" | "NEUTRAL" | "BEARISH",
+  "affectedIndustries": [
+    { "name": "string", "reason": "string (one sentence)" }
+  ],
+  "relatedTickers": [
+    { "ticker": "string", "reason": "string (one sentence)" }
+  ]
+}`;
+
+export class LLMAnalyst {
+  constructor({ logger } = {}) {
+    this.logger = logger ?? { log: console.log, warn: console.warn };
+    this.client = process.env.ANTHROPIC_API_KEY
+      ? new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY })
+      : null;
+  }
+
+  // Analyzes news stories and returns structured market intelligence.
+  // Returns null if ANTHROPIC_API_KEY is not set (graceful degradation).
+  async analyze(stories, existingTickers = []) {
+    if (!this.client) {
+      this.logger.warn('LLMAnalyst: ANTHROPIC_API_KEY not set — skipping analysis');
+      return null;
+    }
+
+    if (!stories?.length) return null;
+
+    const headlines = stories
+      .slice(0, 15)
+      .map((s, i) => `${i + 1}. ${s.title} (${s.publisher ?? 'unknown'})`)
+      .join('\n');
+
+    const userMessage = `Today's market news headlines:\n\n${headlines}\n\nAlready identified catalyst tickers: ${existingTickers.join(', ') || 'none'}`;
+
+    try {
+      const response = await this.client.messages.create({
+        model: 'claude-haiku-4-5',
+        max_tokens: 1024,
+        system: SYSTEM_PROMPT,
+        messages: [{ role: 'user', content: userMessage }],
+      });
+
+      const raw = response.content[0]?.text ?? '';
+      const cleaned = raw
+        .replace(/^```(?:json)?\s*/i, '')
+        .replace(/```\s*$/i, '')
+        .trim();
+      return JSON.parse(cleaned);
+    } catch (err) {
+      this.logger.warn('LLMAnalyst: analysis failed —', err.message);
+      return null;
+    }
+  }
+}