How Lince indexes the crypto mindshare economy.
Crypto markets are driven by narrative velocity and capital rotation. Lince turns raw, unstructured chatter across 6 social networks into verifiable on-chain divergence signals—without retaining user data or selling private order flow.
The 6 stages of signal synthesis.
Cross-Platform Social Telemetry Ingestion
Continuous multi-channel ingestion bypassing rate limits and algorithmic echo chambers.
- •Monitors 6 live conversation networks: X (Twitter), Telegram alpha alpha groups, YouTube, Farcaster, Reddit, and TikTok.
- •Indexes over 1,200 token tickers, project handles, and contract addresses concurrently.
- •Proprietary anti-sybil heuristic strips bot spam, paid shill campaigns, and artificial volume loops.
Mindshare Normalization & Attention Velocity
Converting raw noisy posts into normalized market share of cognitive attention.
- •Mindshare (%) represents a token or sector's exact proportion of total active crypto conversation.
- •Tracks 24h attention velocity to pinpoint which sectors are gaining exponential social momentum.
- •Applies semantic polarity scoring (0.00 to 1.00) to distinguish organic accumulation from FUD.
On-Chain DEX Liquidity Cross-Indexing
Grounding social hype in decentralized liquidity pool telemetry.
- •Polls Uniswap v3, Raydium, Aerodrome, and Curve pools across Base, Solana, Arbitrum, and Ethereum.
- •Correlates attention spikes against actual on-chain DEX trading volume and market capitalization.
- •Filters out illiquid honeypots and low-float manipulation before signals are generated.
Alpha Divergence Scoring Algorithm
Spotting the mathematical disconnect between rising attention and lagging price.
- •Calculates the Divergence Score (0–100): high social spike with compressed price = early accumulation.
- •Factor in Tier-1 smart followers and research KOL citations to weight conviction.
- •Flags tokens in early accumulation stage 12 to 48 hours before broad market discovery.
Zero-Retention Inference via Venice AI
Institutional intelligence without leaking user proprietary prompts or theses.
- •Decentralized inference powered by Venice AI (Llama 3.3 70B & DeepSeek R1).
- •Zero data retention: no prompt storage, IP logging, or training on user queries.
- •Built-in deterministic heuristics engine ensures complete functionality at Rp 0 cost without keys.
Model Context Protocol (MCP) Distribution
Direct JSON-RPC 2.0 streaming into AI coding agents and autonomous trading bots.
- •Exposes live tools: lince_get_narratives, lince_get_alpha_divergence, and lince_get_kols.
- •Native integration into Cursor (~/.cursor/mcp.json), Claude Desktop, and Windsurf.
- •Autonomous agents can programmatically query market mindshare as tool-calls within development loops.
The Alpha Divergence formula.
In efficient markets, asset prices quickly incorporate information. In decentralized crypto networks, social attention precedes price discovery by several hours to days. We quantify this delay mathematically.
| SCORE RANGE | SIGNAL CLASSIFICATION | INTERPRETATION | EXPECTED TIMEFRAME |
|---|---|---|---|
| 90 – 100 | EARLY_ACCUMULATION | Massive attention disconnect. Smart capital accumulation before DEX price reaction. | 12h – 48h |
| 75 – 89 | NARRATIVE_BREAKOUT | Sector-wide thematic expansion. Multiple key projects sharing synchronized velocity. | 24h – 72h |
| 60 – 74 | KOL_CONSENSUS | Multiple verified research analysts publishing independent theses concurrently. | 2d – 5d |
Explore the live intelligence streams.
Test queries in plain English or connect the open Model Context Protocol (MCP) server to your IDE.