Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Generate modular, data-backed market reports (AM/PM) across global assets. Use for daily market briefs, premarket/aftermarket summaries, cross-asset dashboards, sector/asset trend tables, top movers (gainers/losers) blocks, and a single best-idea wrap-up. Designed to be region-agnostic and configurable (tickers/regions/assets).
Generate modular, data-backed market reports (AM/PM) across global assets. Use for daily market briefs, premarket/aftermarket summaries, cross-asset dashboards, sector/asset trend tables, top movers (gainers/losers) blocks, and a single best-idea wrap-up. Designed to be region-agnostic and configurable (tickers/regions/assets).
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Create a concise but information-dense market report that is modular (can include/exclude sections) and data-backed (prices/returns/trend state when possible).
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 + userβs preferred ETFs/tickers Movers source: which exchange/market and where to get movers Risk appetite: conservative vs aggressive framing If the user doesnβt specify, default to a broad global dashboard with US indices, USD, oil, gold, BTC/ETH.
TL;DR (3β6 bullets) Equities (by region) Rates (2Y/10Y + key central bank watch) FX (DXY or major pairs; local pair for user) Commodities (WTI/Brent, gold, copper; add relevant) Crypto (BTC/ETH + anything user cares about) Top movers (top gainers/losers for a chosen exchange) Patterns / trend box (BUY/SELL/WAIT labels for selected instruments) One best idea (cross-asset; include invalidation)
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.
If yfinance isnβt 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.
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.
scripts/price_tape.py: pull prices + returns + MA/RSI for a ticker list (yfinance) scripts/movers_yahoo.py: free Yahoo Finance screeners for top gainers/losers/actives (best-effort) scripts/tmx_movers.py: example movers scraper (TMX Money) you can adapt or swap scripts/render_example.md: a template you can reuse Only run scripts if you actually need structured output; otherwise write the report directly.
Donβt place trades. Avoid certainty language. Use βpattern / bias / invalidation.β If the user asks for explicit buy/sell instructions, provide a conceptual plan + risks. Remind about tax/fees only when relevant.
Trading, swaps, payments, treasury, liquidity, and crypto-financial operations.
Largest current source with strong distribution and engagement signals.