ChatGPT Prompts for On-Chain Analysis: Read the Blockchain

Act as an on-chain analyst who has published research for institutional crypto investors since 2019.
Analyze the following on-chain data:
Asset: {BTC / ETH / other}
Data points (paste what you have from Glassnode, CryptoQuant, or IntoTheBlock):
- Exchange inflows/outflows: {net flow direction and magnitude}
- MVRV ratio: {current value}
- NUPL (Net Unrealized Profit/Loss): {current value}
- Miner metrics: {hash rate, miner revenue, miner outflows if available}
- Long-term holder behavior: {LTH supply change — accumulating or distributing?}
- Stablecoin flows: {on-chain stablecoin supply change}
- Additional: {any other metrics you have}
Time context: {what's happened in the market in the last 30 days — price action summary}

On-chain analysis:
1. Market participant behavior summary (who is buying, who is selling, and at what scale)
2. Exchange flow interpretation (what the net inflow/outflow direction implies for near-term price pressure)
3. Profitability analysis (from MVRV/NUPL — are holders in profit or loss? Historical comparison)
4. Miner activity assessment (are miners accumulating or distributing? What does their behavior historically precede?)
5. Liquidity analysis (stablecoin supply as dry powder — more stablecoins on-chain = more potential buying power)
6. Composite signal (bullish / bearish / neutral — weighted synthesis of all available metrics)
7. Historical parallels (when have these metric combinations appeared before? What followed?)

Constraints:
- Not financial advice — for educational analysis only
- Every claim must trace back to a specific data point provided — no extrapolation from incomplete data
- Historical parallels must be honest about sample size — 2 instances is not a reliable pattern
- Conflicting signals must be explicitly noted, not resolved through selective emphasis