Measure divergence
Focus on where attention and on-chain participation move together—or split apart—instead of only ranking trending tokens.
SOLANA / ATTENTION INTELLIGENCE
Time moves.
Markets reveal.
LAG measures the gap between market attention and on-chain participation. Its core idea: a Narrative Lag Index that compares two streams instead of simply ranking what is trending.
CONCEPT PROTOTYPE · SAMPLE SIGNALS ONLY
THE ATTENTION GAPTalk ≠ activity
NARRATIVE
VELOCITY ↘ ON-CHAIN REALITY
VELOCITY ↘ ON-CHAIN REALITY
THE THESIS / 01
The loudest story
isn't always the
strongest signal.
Social attention can race ahead of actual activity. On-chain behavior can change before the timeline notices. LAG's proposed job is to measure the gap between those streams and show the evidence behind it.
Instead of claiming to predict price, LAG would help users ask better questions: Is attention broadening? Are unique wallets participating? Is liquidity keeping up? Is the move concentrated in a few wallets?
“The gap is the signal.
Context is the edge.”
Context is the edge.”
SIGNAL BOARD / 02
Two streams.
One attention gap.
The chart below is illustrative. The live pulse section uses public market data where the endpoint is available; social attention is not connected yet.
DIVERGENCE MONITOR ILLUSTRATIVE DEMO
Attention velocity+38%
On-chain participation+11%
↗
SAMPLE INTERPRETATIONAttention is accelerating faster than on-chain participation.
A real version would show sources, sample size, confidence, and wallet concentration before drawing conclusions.
NO BUY / SELL SIGNALSSOURCE-LINKED EVIDENCECONFIDENCE LABELS
Demo controls change the illustrative view only. It is not a trading signal.
LIVE MARKET PULSE / 03
Start with the
observable stream.
A free, keyless public endpoint can provide market snapshots. This does not measure social attention and is not the finished Narrative Lag Index.
Market data will appear here
Tap “Load latest data” to request recent token profiles and available pair metrics from DexScreener's public API.
LAG Activity Score is a transparent heuristic based on available 24h volume, liquidity, and price movement. It is not a prediction, not a social-attention measure, and not a buy/sell recommendation.
Source: DexScreener public API. Data may be delayed, incomplete, or unavailable. Market cap and FDV are different measures. Activity scores are transparent heuristics, not predictions. Token listings are not endorsements.
WHAT MAKES IT DIFFERENT / 03
Show the receipts
Every future signal should link to its underlying market data and clearly state what is measured versus inferred.
Explain, don't predict
AI can summarize evidence and possible explanations without turning uncertain patterns into guaranteed outcomes.
BUILD PATH / 04
Prove the signal
before the story.
LAG should earn trust through a useful tool, not just a polished launch page. The first test is whether cross-signal divergence adds information beyond an existing trending dashboard.
01
Prototype & feedback
Brand, layout, and testable user flows.
02
Public market data
Pairs, liquidity, volume, transactions, timestamps, and source links.
03
Attention comparison
Permitted social inputs paired with transparent on-chain metrics.
04
AI evidence briefs
Short explanations with citations, confidence, and limitations.
IMPORTANT
Similar narrative-intelligence tools already exist. LAG's differentiation must come from measuring cross-signal divergence well, explaining it transparently, and making the interface genuinely useful—not from claiming to be first.