Bloom Data

bloom-data — Foundation

Every number comes from Bloom's financial data. Not a language model's training data.

This skill is the shared foundation. Every other Bloom skill reads this first. It defines the rules, checks prerequisites, and lists every available CLI command.

Step 0: Prerequisites Check

Before running any bloom command, verify:

1. CLI is installed

bloom --help
# or, if not globally installed:
npx @bloomai/cli --help

If that fails:

npm install -g @bloomai/cli

2. Authentication is set up

Option A — API key (preferred for automation):

export BLOOM_API_KEY=your_key_here

Option B — Interactive login:

bloom auth login

3. Test it works

bloom info AAPL

You should see Apple's stock data. If you see an auth error, run bloom auth login.

Output Rules

These rules apply to every skill that builds on bloom-data:

1. Always save to file. Use -o /tmp/bloom/<descriptive-name>.json for every command. This keeps the raw JSON out of your context window.

   mkdir -p /tmp/bloom
   bloom info AAPL -o /tmp/bloom/research-info.json
   

2. Use jq to extract only what you need. Don't load entire JSON files into context. Pull the specific fields:

   cat /tmp/bloom/research-info.json | jq '.price, .pe_ratio, .market_cap'
   

3. Never estimate or hallucinate financial data. If the CLI returns no data, say so. Don't fill in numbers from training data.

4. Cite source commands. When presenting a key number, note where it came from:

   • "P/E 33.2 (via bloom info AAPL)"
   • "Revenue grew 12% YoY (via bloom financials AAPL --type revenue)"

5. Create the output directory first:

   mkdir -p /tmp/bloom
   

Available Commands

Full reference for every bloom CLI command.

bloom info <TICKER> [TICKER2 ...]

Stock overview: price, market cap, P/E, analyst ratings, sector, summary.

bloom info AAPL
bloom info AAPL MSFT GOOGL          # batch up to 10 tickers
bloom info NVDA -o /tmp/bloom/nvda-info.json

Key output fields: symbol, price, change_pct, market_cap, pe_ratio, sector, analyst_consensus, price_target, bottom_line

bloom financials <TICKER> --type <TYPE>

Historical financial metrics. Always specify --type.

bloom financials AAPL --type revenue
bloom financials AAPL --type operating_margin
bloom financials AAPL --type free_cash_flow
bloom financials AAPL --type net_earnings
bloom financials AAPL --type revenue -o /tmp/bloom/aapl-revenue.json

Available types: revenue, revenue_growth, operating_margin, net_earnings, net_earnings_growth, free_cash_flow, free_cash_flow_growth, stock_based_compensation, stock_based_compensation_growth

bloom earnings <TICKER>

Recent earnings history + next earnings date.

bloom earnings AAPL
bloom earnings AAPL -o /tmp/bloom/aapl-earnings.json

Key output fields: next_earnings_date, recent_results, beat_miss_history

bloom catalysts <TICKER>

Upcoming events and catalysts that could move the stock.

bloom catalysts AAPL
bloom catalysts NVDA -o /tmp/bloom/nvda-catalysts.json

Key output fields: catalysts (list with title, description, impact)

bloom technicals <TICKER>

Technical analysis: trend, momentum, support/resistance levels.

bloom technicals AAPL
bloom technicals TSLA -o /tmp/bloom/tsla-technicals.json

Key output fields: trend, momentum, support, resistance, moving_averages, rsi

bloom news <TICKER> [--limit N]

Recent news headlines for a ticker.

bloom news AAPL
bloom news AAPL --limit 5
bloom news AAPL MSFT --limit 3 -o /tmp/bloom/news.json

Default limit: 10. Recommended: --limit 5 for research, --limit 3 for briefings.

Key output fields: list of articles with headline, source, published_at, url, summary

bloom sentiment

Market-wide sentiment: Fear & Greed index, AAII bull/bear survey, VIX.

bloom sentiment
bloom sentiment -o /tmp/bloom/sentiment.json

Key output fields: fear_greed_index, fear_greed_label, aaii_bull, aaii_bear, vix

bloom market --type <TYPE> [--limit N]

Market overview by category.

bloom market --type major_indexes
bloom market --type top_movers --limit 10
bloom market --type sector_performance
bloom market --type major_indexes -o /tmp/bloom/indexes.json

Available types: major_indexes, top_movers, sector_performance

Key output fields:

• major_indexes: list with name, price, change_pct, ytd_change
• top_movers: list with ticker, change_pct, price, reason
• sector_performance: list with sector, change_pct

bloom portfolio '<json>'

Analyze a portfolio. Input is a JSON object with ticker:weight pairs.

bloom portfolio '{"AAPL": 0.4, "MSFT": 0.3, "GOOGL": 0.3}'
bloom portfolio '{"NVDA": 0.5, "TSLA": 0.25, "AMD": 0.25}' -o /tmp/bloom/portfolio.json

Weights should sum to 1.0. Key output fields: grade, concentration_risk, sector_breakdown, correlation, suggestions

bloom screen "<filter>" ["<filter2>" ...]

Screen for stocks matching criteria.

bloom screen "market_cap > 10B" "pe_ratio < 20" "revenue_growth > 10"
bloom screen "dividend_yield > 3" "payout_ratio < 60"
bloom screen "market_cap > 10B" "pe_ratio < 20" -o /tmp/bloom/screener.json

Common filters: market_cap > XB, pe_ratio < X, revenue_growth > X, dividend_yield > X, payout_ratio < X

Key output fields: list of matches with ticker, pe_ratio, revenue_growth, market_cap

bloom collections [--section <SECTION>]

Curated stock lists by theme.

bloom collections
bloom collections --section VALUE
bloom collections --section GROWTH
bloom collections --section DIVIDEND
bloom collections -o /tmp/bloom/collections.json

Available sections: VALUE, GROWTH, DIVIDEND, MOMENTUM, DEFENSIVE

Key output fields: list of collection entries with ticker, name, reason, score when available

bloom ai-trades [--limit N]

Trades made by AI models in the AI Arena (real money, live portfolios).

bloom ai-trades
bloom ai-trades --limit 10 -o /tmp/bloom/ai-trades.json

Key output fields: trades (list with model, ticker, direction, return_pct, date)

bloom ai-portfolio

Current holdings of each AI model in the Arena.

bloom ai-portfolio
bloom ai-portfolio -o /tmp/bloom/ai-portfolio.json

Key output fields: portfolios (keyed by model name, with holdings, total_return, cash_pct)

bloom trades "<thesis>"

Evaluate a trade thesis. Pass a natural language description.

bloom trades "buy NVDA before next earnings because AI spending is accelerating"
bloom trades "short TSLA because valuation is stretched" -o /tmp/bloom/check-eval.json

Key output fields: verdict, bull_case, bear_case, risk_reward, supporting_data

bloom position-size --bull <est> --bear <est> --conviction <score> [--value <portfolio-value>]

Calculate appropriate position size based on risk/reward.

bloom position-size --bull 20 --bear 10 --conviction 7
bloom position-size --bull 30 --bear 15 --conviction 8 --value 100000 -o /tmp/bloom/sizing.json

• --bull: estimated upside % if thesis is right
• --bear: estimated downside % if thesis is wrong
• --conviction: score 1-10
• --value: optional portfolio value in dollars

Key output fields: position_pct, max_loss_pct, risk_reward_ratio, dollar_amount (if value provided)

Error Handling

Related Skills

• research — Full stock analysis using bloom commands
• review — Portfolio grading and suggestions
• discover — Finding new opportunities
• check — Evaluating a specific trade
• briefing — Daily market update