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My morning BTC checklist uses three agents — here's what it actually said the day BTC bottomed

A solo developer built a morning Bitcoin checklist using three specialized agents—technical, on-chain, and macro—that run in parallel to score the market and generate a single action signal. The system, which runs at 6:30 AM IST, would have issued a STRONG_BUY signal on the day BTC bottomed at $76,099, recommending a full position. The developer emphasizes that the multi-agent approach reduces decision fatigue and provides a disciplined framework to avoid trading when signals disagree.

read4 min publishedJun 15, 2026

I am not a quant. I am a solo developer who holds BTC and doesn't trust Twitter, TradingView gurus, or a single indicator to make a 4-figure trade decision.

So I built a morning checklist: three specialized agents (technical, on-chain, macro) run in parallel, score the market, and a signal generator combines them into one action line. It runs at 6:30 AM IST before I touch my phone. Below is what it looks like end-to-end — and what it would have told me on the day BTC actually bottomed.

GitHub: https://github.com/AmSach/btc-research

cd ~/projects/btc-research
python3 scripts/run_analysis.py

That's it. One command. Three agents fire in parallel:

[1/4] Running Technical Analysis Agent...
  Signal: NEUTRAL | Score: 0.44 | Conf: 0.65
[2/4] Running On-Chain Analyst Agent...
  Signal: BULLISH | Score: 0.80 | Conf: 0.71
[3/4] Running Macro Strategist Agent...
  Signal: BULLISH | Score: 0.75 | Conf: 0.69
[4/4] Generating Combined Signal...

Eight seconds later, I get a single decision in my terminal — and an email copy in my inbox before the kettle finishes boiling:

Signal Type: BUY Total Score: 0.662 Confidence: 0.684 Action: Take partial position (25-50% of capital) Price: $76,099

Agent Scores: Technical 0.440 (weight: 0.35) On-Chain 0.800 (weight: 0.40) Macro 0.750 (weight: 0.25)

Key Drivers: • On-Chain: bullish (0.8) • Macro: bullish (0.75)

Risk Factors: (none flagged)

Key Levels: support $68,900 resistance $75,000 ema_200 $82,919 ath $125,835


I make a coffee. I open my exchange. I act. No Twitter. No "BTC to the moon" Telegram groups. No waffling because the candle looked "weird."

The problem is not "I don't have a strategy." Most retail traders have a strategy. The problem is **decision fatigue under uncertainty**:

The three-agent setup forces me to look at three independent angles and a single weighted verdict. On a typical day, the agents disagree, and the system spits out NEUTRAL — I do nothing. The most valuable output is the permission to **not trade** when the signals don't agree.

Let's pretend I had this running on the day BTC bottomed after the ETF-flow scare:

{ "timestamp": "2026-01-09T01:00:00", "technical": {"signal": "OVERSOLD", "score": 0.72, "confidence": 0.78}, "onchain": {"signal": "BULLISH", "score": 0.78, "confidence": 0.74}, "macro": {"signal": "BULLISH", "score": 0.85, "confidence": 0.80}, "signal_type": "STRONG_BUY", "total_score": 0.79, "confidence": 0.77, "action": "Take full position (50-100% of capital)", "key_drivers": [ "Technical: oversold (0.72)", "On-Chain: bullish (0.78)", "Macro: bullish (0.85)" ] }


Three independent agents all green. RSI oversold, exchange reserves at multi-year low, DXY rolling over. The signal generator says **STRONG_BUY, take full position**. That was the morning I would have actually added to my position instead of doom-scrolling.

The same pipeline, run a week later with macro turning neutral, would have said NEUTRAL — and the right call was to stop adding.

I deliberately did **not** use one LLM to "just look at the chart." Three reasons:

**Separation of forces.** Technical analysis is pattern math, on-chain is network-state data, macro is correlation. A single LLM blends them by vibes. Three narrow scoring functions plus a weighted combiner is auditable.

**Confidence is calibrated per agent.** Technical is honestly 65-75% confident because RSI is noisy. On-chain is 70-80% because exchange reserves are slow-moving. Macro is 60-70% because DXY can flip on a Fed tweet. The signal generator weights by both score *and* confidence, so a high-confidence on-chain signal (0.8, 0.71) overrides a low-confidence technical one (0.44, 0.65).

**I can disable a broken agent.** When Glassnode's API went down in March, I commented out one line and the other two still ran with rebalanced weights. Try doing that with a monolithic prompt.

THRESHOLDS = { 'strong_buy': 0.75, 'buy': 0.60, 'neutral': 0.45, 'sell': 0.30 }

total_score = sum( agent['score'] * weight for agent, weight in zip(agents, [0.35, 0.40, 0.25]) )


That's the whole thing. The point is not cleverness — the point is **I see the rules, I can override them, and I can rewrite them on a Sunday afternoon when I disagree with a weight.**

It is **not** for day traders, leverage addicts, or anyone who thinks a 0.66 score is a substitute for risk management.

The weights are obviously debatable. Right now on-chain > technical > macro because I think the slow money is the smart money. If you think macro should dominate (DXY leads everything), or technical should dominate (price action is truth), fork it, change `AGENT_WEIGHTS`

in `scripts/config.py`

, and tell me why. I read every issue.

**GitHub:** [https://github.com/AmSach/btc-research](https://github.com/AmSach/btc-research)

**Skill file:** `skills/btc_system/SKILL.md`

(drop it into any agent runtime)

*Three agents, one signal, one email, zero Telegram groups. Built because I needed it, open-sourced because you might too.*
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