check

name

check

description

Evaluate a specific trade idea. Takes a natural language thesis ("I want to buy NVDA before earnings"), runs data against it, and returns a verdict with bull/bear case, key numbers, and position sizing. Triggers: "should I buy AAPL", "is this trade dumb", "check this trade", "I'm thinking of buying TSLA", "evaluate this trade", "is NVDA a good buy right now", "I want to short META", "analyze my trade idea", "what do you think of buying AMD", "is it too late to buy MSFT"

check — Evaluate a Trade

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

Trigger: /check <TRADE_THESIS> — when a user describes a trade they're considering.

The thesis can be:

• A simple buy: "buy AAPL"
• A directional idea: "short TSLA because valuation is stretched"
• A thesis with context: "buy NVDA before next earnings because AI spending is accelerating"
• A question: "should I buy META right now?"

---

Read bloom-data Skill First

Before running anything, check that bloom is installed and authenticated. See the bloom-data skill for prerequisites and output rules.

mkdir -p /tmp/bloom

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Step 0: Parse the Trade

Before running any commands, extract:

1. Ticker — the stock symbol (e.g., NVDA)
2. Direction — Buy (long) or Sell/Short?
3. Thesis — the reason or context (if any)
4. Time horizon — short-term trade vs. longer hold? (infer if not stated)

If no ticker is clear, ask the user to clarify before proceeding.

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Steps (Run in Order)

1. Company overview

bloom info <TICKER> -o /tmp/bloom/check-info.json

2. AI thesis evaluation

bloom trades "<full thesis from user>" -o /tmp/bloom/check-eval.json

Pass the user's actual words. The more specific, the better.

3. Technical picture

bloom technicals <TICKER> -o /tmp/bloom/check-technicals.json

4. Revenue growth trend

bloom financials <TICKER> --type revenue_growth -o /tmp/bloom/check-revenue-growth.json

5. Earnings history + next date

bloom earnings <TICKER> -o /tmp/bloom/check-earnings.json

6. Upcoming catalysts

bloom catalysts <TICKER> -o /tmp/bloom/check-catalysts.json

7. Position sizing

bloom position-size --bull <upside_est> --bear <downside_est> --conviction <score> -o /tmp/bloom/check-sizing.json

Estimate --bull and --bear from the data:

• Bull: analyst price target upside % (from bloom info)
• Bear: estimated downside if thesis is wrong (use recent pullback or support level distance)
• Conviction: 1-10 based on quality of data supporting the thesis (not gut feel — data quality)

8. Extract key fields

# Core info
cat /tmp/bloom/check-info.json | jq '{price, pe_ratio, market_cap, analyst_consensus, price_target, sector}'

# Thesis evaluation
cat /tmp/bloom/check-eval.json | jq '{verdict, bull_case, bear_case, risk_reward, supporting_data}'

# Technicals
cat /tmp/bloom/check-technicals.json | jq '{trend, momentum, rsi, support, resistance}'

# Revenue growth trend (YoY, last 4 periods)
cat /tmp/bloom/check-revenue-growth.json | jq '.[-4:]'

# Next earnings
cat /tmp/bloom/check-earnings.json | jq '{next_earnings_date, recent_results}'

# Top catalysts
cat /tmp/bloom/check-catalysts.json | jq '.catalysts[:3]'

# Sizing
cat /tmp/bloom/check-sizing.json | jq '{position_pct, risk_reward_ratio, max_loss_pct}'

---

Verdict Framework

Verdict	When to use
✅ Looks Good	Data supports the thesis, risk is manageable, technicals aren't screaming "don't"
⚠️ Proceed With Caution	Thesis has merit but there are real concerns — maybe size down, wait for a trigger
🛑 Rethink This	Data contradicts the thesis, or the risk/reward is poor

Be honest. Most trade ideas are somewhere in the middle. ⚠️ is the most common answer.

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Output Format

## Trade Check: [Buy/Short] $[TICKER] at $[Price]

### Verdict: [✅ Looks Good / ⚠️ Proceed With Caution / 🛑 Rethink This]

### Your Thesis
"[User's original thesis, quoted exactly]"

### What The Data Says

**For it:**
1. [Strongest data point supporting the trade]
2. [Second supporting point]
3. [Third supporting point]

**Against it:**
1. [Strongest counter-argument from data]
2. [Second concern]
3. [Third concern]

### Key Numbers
| Metric | Value | Signal |
|--------|-------|--------|
| Current Price | $[X] | |
| Analyst Target | $[X] ([X]% upside) | 🟢/🟡/🔴 |
| P/E Ratio | [X] | 🟢/🟡/🔴 |
| Revenue Trend | [X]% YoY | 🟢/🟡/🔴 |
| Analyst Consensus | [X Buy / X Hold / X Sell] | 🟢/🟡/🔴 |
| Technical Trend | [Bullish/Bearish/Neutral] | 🟢/🟡/🔴 |

### Timing
**Next earnings:** [Date — or "no date set yet"]
[One sentence: does timing help or hurt this trade? Buying before earnings is a bet on the report.]

**Key levels:**
- Support: $[X] — [what happens if it breaks?]
- Resistance: $[X] — [what's the next target if it clears?]

**Upcoming catalysts:** [Top 1-2 from bloom catalysts]

### If You Do It
**Suggested size:** [X]% of portfolio
**Risk/reward:** [X]:1
**Where to stop out:** $[X] ([X]% below current price)
**What would change the thesis:** [One sentence — what data would make you exit?]

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*Data from Bloom CLI. Source commands: bloom info, bloom trades, bloom technicals, bloom financials, bloom earnings, bloom catalysts, bloom position-size.*

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Notes

• Don't let a user talk you into a 🟢 when the data says 🔴. The point is honest evaluation.
• "Proceed With Caution" isn't a cop-out — be specific about what the caution is.
• If the user's thesis is vague ("AAPL seems cheap"), run the data and help them form a real thesis based on what you find.
• Position sizing is the most ignored part of any trade. Always include it.
• If earnings are within 2 weeks, always flag that. Earnings = binary event = higher risk.

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Related Skills

• bloom-data — Prerequisites and CLI reference (read this first)
• research — Full deep dive if you want more context before deciding
• briefing — Check market conditions before entering a trade
• discover — If this one doesn't check out, find something that does