Build integrated IS/BS/CF financial workbooks in Excel.
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Stock quotes, history, search, compare, crypto via Yahoo.
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Review the instructions the agent will receive before you install.
Read-only market data via Yahoo Finance. Five commands: quote, search,
history, compare, crypto. Python stdlib only — no API key, no pip
installs. Yahoo's endpoint is unofficial and may rate-limit or change.
Python 3.8+ stdlib only. Optional: set ALPHA_VANTAGE_KEY to enrich
market_cap, pe_ratio, and 52-week levels when Yahoo's crumb-protected
fields come back null. Free key: https://www.alphavantage.co/support/#api-key
Invoke through the terminal tool. Once installed:
SCRIPT=~/.openamer/skills/finance/stocks/scripts/stocks_client.py
python3 $SCRIPT quote AAPL
All output is JSON on stdout — pipe through jq if you want to slice it.
python3 $SCRIPT quote AAPL
python3 $SCRIPT quote AAPL MSFT GOOGL TSLA
python3 $SCRIPT search "Tesla"
python3 $SCRIPT history NVDA --range 6mo
python3 $SCRIPT compare AAPL MSFT GOOGL
python3 $SCRIPT crypto BTC ETH SOL
quote SYMBOL [SYMBOL2 ...]Current price, change, change%, volume, 52-week high/low.
search QUERYFind tickers by company name. Returns top 5: symbol, name, exchange, type.
history SYMBOL [--range RANGE]Daily OHLCV plus stats (min, max, avg, total return %). Ranges: 1mo,
3mo, 6mo, 1y, 5y. Default: 1mo.
compare SYMBOL1 SYMBOL2 [...]Side-by-side: price, change%, 52-week performance.
crypto SYMBOL [SYMBOL2 ...]Crypto prices. Pass BTC (the script appends -USD automatically).
market_cap and pe_ratio may return null on quote when Yahoo's
crumb session isn't established. Set ALPHA_VANTAGE_KEY to backfill.python3 ~/.openamer/skills/finance/stocks/scripts/stocks_client.py quote AAPL
Returns a JSON object with symbol: "AAPL" and a numeric price field.
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Build integrated IS/BS/CF financial workbooks in Excel.
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Run and grow the OpenAmer Agent-to-Agent swarm: identity, trust, node-to-node ask, signed skill/insight sharing, and the autonomous self-learning loop.
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Use for A/B experiments on OpenAmer configs and skills.
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Roleplay a hostile user to find and triage UX pain points.
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Agent mesh: master/worker nodes, HTTP delegation, heartbeat.
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Use for agentic commerce payments tasks. Candidate synthesized from trend radar; awaiting trial promotion.
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