Snorfle

$SNORFLE

Solana meme token hype cycle tracker. Every meme token has a lifecycle. It pumps. It peaks. It dies. Snorfle classifies where it actually is.

DORMANTEMERGINGPUMPINGPEAKED

> The mistake most people make is entering at the peak because that's when it feels most alive — maximum volume, maximum price action, maximum noise. Snorfle measures where a token actually is in that cycle. Not where it feels like it is.

> The Four Signals

price_surge_signal35%

|1h price change| >= 20% triggers

volume_spike_signal30%

1h volume >= 3x hourly baseline

holder_velocity_signal20%

Holder count grew >= 5% vs snapshot

organic_traction_signal15%

holders / (mcap/1000) >= 10

All four weighted and averaged → hype score 0-100 → phase classification.

> Phase Classification

ScorePhase
0-25DORMANT
26-50EMERGING
51-75PUMPING
76-100PEAKED

> Usage

from snorfle import track, MemeSnapshot

snap = MemeSnapshot(
    token_mint="SnflXyz...pump",
    symbol="SNORFLE",
    price_usd=0.00042,
    price_change_1h_pct=38.0,
    price_change_24h_pct=120.0,
    volume_1h=180_000,
    volume_24h=900_000,
    volume_prev_24h=150_000,
    holder_count=2800,
    holder_count_prev=2100,
    market_cap_usd=420_000,
)

report = track(snap)

print(report.phase)       # PUMPING
print(report.hype_score)  # ~71.4
print(report.insight)     # "Active hype cycle..."
pip install snorflePure Python 3.10+

> Why Price Surge Gets 35%

On Solana meme tokens, the 1-hour price change is the most immediate signal of active hype. Volume can be faked. Holder count can be slow to update. But a sharp move in price — up or down — means someone is paying attention right now.

The signal uses absolute value because dumps generate hype too. A token crashing 40% in an hour has more attention than a token sitting flat with decent volume. Attention is the resource. Snorfle measures it.

Track the cycle. Know the phase.

Stop aping at the top. Snorfle tells you where you are in the hype cycle before you commit capital.

133 Tests|MIT License|Python + TypeScript