market-oracle_skill

This skill analyzes breaking news and market data across metals, oil, crypto, and stocks to predict short, medium, and long-term ripple effects.
  • Python

2.5k

GitHub Stars

4

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill market-oracle

  • _meta.json279 B
  • config.example.json121 B
  • setup.sh1.0 KB
  • SKILL.md7.1 KB

Overview

This skill is Market Oracle, a financial event impact analyzer that fetches breaking news and live market data across metals, oil, crypto, and stocks. It generates a structured three-layer prediction of short-, medium-, and long-term market ripple effects tied to specific events. The output is concise, quantified where possible, and includes risk caveats.

How this skill works

The skill collects real-time news and price data, then runs a three-layer analysis pipeline to map immediate, 1–12 hour, and 12–24 hour impacts. It cross-references asset correlations, trading volumes, and time-zone effects to produce directional and magnitude estimates. Results include likely follow-up events, sector contagion paths, and contrarian risk factors.

When to use it

  • When breaking news affects macro or sector fundamentals (central bank moves, OPEC decisions, geopolitical shocks).
  • When monitoring price-sensitive assets: gold, silver, copper, WTI/Brent, BTC/ETH, major indices and large-cap tickers.
  • Before or during trading sessions to anticipate opening gaps and intraday volatility.
  • When you need quantified, time-horizon based scenarios rather than a single directional opinion.

Best practices

  • Provide a clear event description or URL for accurate context and extraction.
  • Specify asset focus if you want a narrower analysis (e.g., oil,gold,btc).
  • Use the live market-data option for freshest price inputs; permit at least 1–5 minutes for data fetch.
  • Treat predictions as probabilistic ranges and note contrarian triggers listed in the output.
  • Combine these analyses with your own risk management; do not treat them as trading advice.

Example use cases

  • Analyze a Fed rate announcement and predict immediate FX, gold, and equity reactions.
  • Assess an OPEC supply decision and map knock-on effects to airlines, refinery margins, and regional stocks.
  • Evaluate a major hack or regulatory announcement in crypto and estimate short/medium liquidity impacts.
  • Monitor sudden geopolitical events and produce three-layer scenarios for oil, gold, and global indices.

FAQ

It produces three horizons: short (minutes to 1 hour), medium (1–12 hours), and long (12–24 hours).

Can I focus the analysis on specific assets?

Yes. Provide a comma-separated focus list (e.g., oil,gold,btc) to concentrate analysis and model outputs on those assets.

Are these recommendations actionable trading advice?

No. Outputs are probabilistic analyses for information and education only. They are not buy/sell recommendations.

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