Modular Market Brief

Create a concise but information-dense market report that is modular (can include/exclude sections) and data-backed (prices/returns/trend state when possible).

Inputs to ask for (or assume defaults)

• - Time window: AM (since prior close) vs PM (what changed since AM)
• Regions: e.g., US, Canada, EU, Asia (user chooses)
• Asset blocks: equities, rates, FX, commodities, crypto
• Core tickers: indices + user’s preferred ETFs/tickers
• Movers source: which exchange/market and where to get movers
• Risk appetite: conservative vs aggressive framing

If the user doesn’t specify, default to a broad global dashboard with US indices, USD, oil, gold, BTC/ETH.

Report structure (recommended)

1) TL;DR (3–6 bullets) 2) Equities (by region) 3) Rates (2Y/10Y + key central bank watch) 4) FX (DXY or major pairs; local pair for user) 5) Commodities (WTI/Brent, gold, copper; add relevant) 6) Crypto (BTC/ETH + anything user cares about) 7) Top movers (top gainers/losers for a chosen exchange) 8) Patterns / trend box (BUY/SELL/WAIT labels for selected instruments) 9) One best idea (cross-asset; include invalidation)

Data guidance

Prefer programmatic price tape when available:

• - Use yfinance for tickers/ETFs/crypto/commodity futures (optional dependency).
• If a market needs a dedicated movers list, use a web source (exchange site / finance portal) and then enrich tickers via yfinance.

Installing yfinance (recommended, but not required)

If yfinance isn’t available, the skill can still produce a narrative brief from public sources.

For reliable installs on modern Linux distros (PEP 668), prefer a venv:

python3 -m venv ~/.venvs/market-brief
~/.venvs/market-brief/bin/pip install -U pip
~/.venvs/market-brief/bin/pip install yfinance pandas numpy

Then run scripts using ~/.venvs/market-brief/bin/python.

Trend labeling (simple + explainable)

Use MA/RSI-based state labels:

• - BUY: close > MA20 > MA50 and RSI(14) >= 50
• SELL: close < MA20 < MA50 and RSI(14) <= 50
• WAIT: everything else

Always present it as a pattern (not a guarantee) and include a one-line rationale.

Bundled scripts (optional helpers)

• - scripts/price_tape.py: pull prices + returns + MA/RSI for a ticker list (yfinance)
• INLINECODE2: free Yahoo Finance screeners for top gainers/losers/actives (best-effort)
• INLINECODE3: example movers scraper (TMX Money) you can adapt or swap
• INLINECODE4: a template you can reuse

Only run scripts if you actually need structured output; otherwise write the report directly.

Safety / finance guardrails

• - Don’t place trades.
• Avoid certainty language. Use “pattern / bias / invalidation.”
• If the user asks for explicit buy/sell instructions, provide a conceptual plan + risks.
• Remind about tax/fees only when relevant.