{"categories":[{"slug":"smart-money","name":"Smart Money & Insider Activity","color":"#D94A4A"},{"slug":"investment-graph","name":"Investment Graph Intelligence","color":"#4A90D9"},{"slug":"defi-risk","name":"DeFi Risk & Opportunity","color":"#059669"},{"slug":"fundamentals","name":"Protocol Fundamentals","color":"#D97706"},{"slug":"governance","name":"Governance Risk","color":"#0284C7"},{"slug":"token-lifecycle","name":"Token Lifecycle Risk","color":"#E11D48"},{"slug":"convergence","name":"Cross-Domain Convergence","color":"#7C3AED"},{"slug":"social","name":"Social & Sentiment","color":"#8B5CF6"},{"slug":"trading","name":"Trading Composites","color":"#F59E0B"},{"slug":"macro","name":"Macro Regime","color":"#DC2626"}],"signals":[{"slug":"insider-accumulation","name":"Insider Accumulation / Distribution","category":"Smart Money & Insider Activity","category_slug":"smart-money","what":"Detects when protocol insiders — team members, early investors, and known affiliated wallets — are systematically buying or selling tokens over a rolling window.","why":"Insiders possess asymmetric information about protocol health. Sustained insider buying often precedes positive catalysts, while coordinated selling can signal internal concerns.","interpretation":{"high":"Large-scale directional flow (>$1M net) with strong buy/sell skew.","moderate":"Moderate insider activity with directional bias.","low":"Minor insider transactions detected."},"frequency":"Daily. Typically 10-30 signals per day.","example":"Protocol X: insider accumulation of $2.4M (47 transactions, 89% buys).","audiences":["trader","vc","institution"]},{"slug":"whale-cross-protocol","name":"Whale Cross-Protocol Activity","category":"Smart Money & Insider Activity","category_slug":"smart-money","what":"Identifies wallets with significant activity across many distinct protocols simultaneously, revealing sector-level thesis bets.","why":"Sophisticated actors diversify across protocols within a thesis. Tracking their cross-protocol footprint reveals emerging sector narratives.","interpretation":{"high":"Wallet active across 15+ protocols.","moderate":"Wallet spanning 10-14 protocols.","low":"Wallet across 8-9 protocols."},"frequency":"Daily. Typically 5-15 whale profiles per scan.","example":"Wallet active across 18 protocols spanning DeFi lending and liquid staking sectors.","audiences":["trader","vc"]},{"slug":"sector-rotation","name":"Sector Capital Rotation","category":"Smart Money & Insider Activity","category_slug":"smart-money","what":"Aggregates insider capital flows by market sector to detect early rotation between sectors.","why":"Sector rotation by informed participants is one of the strongest leading indicators in crypto markets.","interpretation":{"high":"Sector net flow >$5M with strong imbalance.","moderate":"Sector showing $1-5M net flow.","low":"Modest sector-level imbalance detected."},"frequency":"Daily. Typically 3-8 sector signals per scan.","example":"DeFi Lending: net insider inflow of $8.2M (+34% imbalance, 156 transactions).","audiences":["trader","vc","institution"]},{"slug":"flow-anomaly","name":"Daily Flow Anomaly","category":"Smart Money & Insider Activity","category_slug":"smart-money","what":"Statistical outlier detection on daily aggregate insider capital flows using z-scores against a 30-day rolling baseline.","why":"Most days are noise. This signal identifies genuinely anomalous capital movements using statistical methods.","interpretation":{"high":"Z-score >3 — a 3-sigma event.","moderate":"Z-score 2-3 — notably elevated activity.","low":"Z-score 1.5-2 — above-average but within broader variance."},"frequency":"Daily. Typically 2-5 anomaly signals per scan.","example":"April 15: anomalous net outflow of $47M (z-score=+3.2, 892 transactions).","audiences":["trader","institution"]},{"slug":"smart-money-divergence","name":"Smart Money Divergence","category":"Smart Money & Insider Activity","category_slug":"smart-money","what":"Tracks the largest token holders and detects when their 30-day balance change exceeds 20%.","why":"Top holders are the most informed and impactful participants. Their positioning precedes major price movements.","interpretation":{"high":"Top holder balance change >40%.","moderate":"Top holder change 20-40%.","low":"Notable but smaller holder movement detected."},"frequency":"Daily. Typically 15-40 signals per scan.","example":"Token Y: top holder (rank #1, 12.3% ownership) increased balance +34% over 30d.","audiences":["trader","vc"]},{"slug":"co-investment-network","name":"Co-Investment Network","category":"Investment Graph Intelligence","category_slug":"investment-graph","what":"Maps the investment graph to discover token pairs that share three or more investors.","why":"Shared investors create hidden correlations — common capital, common incentives, and common information flow.","interpretation":{"high":"5+ shared investors — deeply interconnected tokens.","moderate":"3-4 shared investors.","low":"Connection detected but with limited overlap."},"frequency":"Daily. Typically 200-500 co-investment pairs per scan.","example":"Token A and Token B share 5 investors: Fund Alpha, Fund Beta, Fund Gamma.","audiences":["vc","institution"]},{"slug":"cross-sector-cluster","name":"Cross-Sector Cluster","category":"Investment Graph Intelligence","category_slug":"investment-graph","what":"Identifies communities of tokens that span three or more market sectors, revealing thematic investment theses.","why":"The most valuable investment theses often span sectors. These cross-sector connections are only visible through graph analysis.","interpretation":{"high":"5+ sectors represented — broad macro thesis.","moderate":"3-4 sectors — meaningful cross-sector connection.","low":"Cluster detected with borderline sector diversity."},"frequency":"Daily. Typically 10-30 clusters per scan.","example":"Cluster of 8 tokens spans 4 sectors: DeFi Lending (3), L1 (2), Liquid Staking (2), Oracle (1).","audiences":["vc","institution"]},{"slug":"bridge-fund","name":"Bridge Fund Detection","category":"Investment Graph Intelligence","category_slug":"investment-graph","what":"Computes network centrality metrics for every fund in the investment graph, identifying funds that connect otherwise separate clusters.","why":"Bridge funds are kingmakers. Their investment in a new project instantly connects it to multiple existing clusters.","interpretation":{"high":"Very high betweenness centrality — connects many separate communities.","moderate":"Notable bridging position in the graph.","low":"Moderate bridging detected."},"frequency":"Daily. Typically 5-15 bridge funds identified per scan.","example":"Fund Z: PageRank=0.0082, Betweenness=0.034. Connects 4 isolated token clusters.","audiences":["vc","institution"]},{"slug":"developer-network","name":"Shared Developer Network","category":"Investment Graph Intelligence","category_slug":"investment-graph","what":"Analyzes code repositories to find projects sharing the same developers and identifies bus factor risk.","why":"Developer talent is the scarcest resource in crypto. Shared developers indicate code dependencies and correlated risk.","interpretation":{"high":"10+ shared developers — deep technical interdependence.","moderate":"5-9 shared developers or 1-2 contributor concentration.","low":"Minor developer overlap or moderate concentration."},"frequency":"Daily. Typically 50-100 overlap pairs per scan.","example":"Token A and Token B share 12 GitHub contributors. Token C has only 1 active contributor.","audiences":["vc","institution"]},{"slug":"yield-anomaly","name":"Yield Anomaly","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Detects unusual APY spikes or collapses in DeFi pools, filtered to pools with >$500K TVL.","why":"Sudden yield changes are early warnings of incentive programs, exploits, or smart money exits.","interpretation":{"high":"APY change >500% — extreme event.","moderate":"APY change 200-500% — significant shift.","low":"APY change 100-200% — notable but may be within normal volatility."},"frequency":"Daily. Typically 5-20 yield anomalies per scan.","example":"Pool XYZ: APY collapsed -340% in 7d (current: 2.1%, TVL: $4.2M).","audiences":["trader","institution"]},{"slug":"yield-sustainability","name":"Yield Sustainability","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Identifies pools where reward token emissions drive the majority of yield (reward APY > 5x base APY).","why":"When reward APY is 10-20x the organic yield, the pool is a token distribution mechanism disguised as a yield opportunity.","interpretation":{"high":"Reward/base ratio >15x — almost entirely emissions.","moderate":"Reward/base ratio 8-15x — emission-heavy.","low":"Reward/base ratio 5-8x — elevated emission dependence."},"frequency":"Daily. Typically 10-30 sustainability warnings per scan.","example":"Pool ABC: reward APY (42.5%) is 17x base APY (2.5%). TVL: $2.8M.","audiences":["trader","institution"]},{"slug":"utilization-stress","name":"Utilization Stress","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Monitors lending protocol utilization rates and flags when utilization exceeds 85%.","why":"Utilization above 85% means lenders cannot withdraw and borrowing rates spike as the interest rate curve enters its steep zone.","interpretation":{"high":"Utilization >95% — critical liquidity stress.","moderate":"Utilization 90-95% — danger zone.","low":"Utilization 85-90% — approaching stress threshold."},"frequency":"Daily. Typically 5-15 protocols flagged per scan.","example":"Protocol X: utilization at 93.2% ($1.8B borrowed of $1.93B deposited).","audiences":["trader","institution"]},{"slug":"debt-ceiling-proximity","name":"Debt Ceiling Proximity","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Detects DeFi lending pools where total borrowing is approaching the governance-set debt ceiling.","why":"Debt ceilings are hard limits. When a pool is at 95% of its ceiling, rate spikes and failed transactions follow.","interpretation":{"high":"Usage >95% of ceiling — borrowing nearly halted.","moderate":"Usage 90-95% — ceiling approaching.","low":"Usage 85-90% — governance action may be needed."},"frequency":"Daily. Typically 3-10 pools flagged per scan.","example":"Pool USDC-ETH: borrowing $48.2M of $50M ceiling (96.4% used).","audiences":["trader","institution"]},{"slug":"stablecoin-depeg","name":"Stablecoin Peg Deviation","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Monitors stablecoin prices for deviations from their target peg, flagging >0.5% deviation with >$1M supply.","why":"Stablecoin depegging is a systemic risk event that cascades through lending protocols, DEX pools, and payment systems.","interpretation":{"high":"Deviation >2% — active depegging event.","moderate":"Deviation 1-2% — significant peg stress.","low":"Deviation 0.5-1% — elevated but may be transient."},"frequency":"Daily. Typically 2-8 depeg alerts per scan.","example":"Stablecoin Z: trading at $0.9847 (1.53% below peg). Circulating: $340M.","audiences":["trader","institution"]},{"slug":"stablecoin-supply-shift","name":"Stablecoin Supply Shift","category":"DeFi Risk & Opportunity","category_slug":"defi-risk","what":"Detects large week-over-week changes in stablecoin circulating supply (>10% with >$1M circulation).","why":"Stablecoin supply is a proxy for capital entering and exiting the crypto ecosystem, preceding market movements.","interpretation":{"high":"Supply change >30% — massive capital flow.","moderate":"Supply change 15-30% — significant flow.","low":"Supply change 10-15% — notable."},"frequency":"Daily. Typically 5-15 supply shift signals per scan.","example":"Stablecoin W: supply expanded +22% week-over-week ($180M increase).","audiences":["trader","vc","institution"]},{"slug":"revenue-momentum","name":"Revenue Momentum","category":"Protocol Fundamentals","category_slug":"fundamentals","what":"Tracks protocol revenue acceleration by comparing 30-day and 90-day revenue change rates.","why":"Revenue is the most honest metric in crypto. Unlike TVL or users, revenue represents real value extraction.","interpretation":{"high":"Revenue accelerating >100% in 30d on strong 90d trend.","moderate":"30d revenue growth >50% diverging from 90d.","low":"Modest momentum shift detected."},"frequency":"Daily. Typically 10-25 momentum signals per scan.","example":"Protocol A: revenue accelerating — 30d +82% vs 90d +35%.","audiences":["trader","vc","institution"]},{"slug":"earnings-health","name":"Earnings Health","category":"Protocol Fundamentals","category_slug":"fundamentals","what":"Identifies protocols with deeply negative earnings (daily losses >$10K) that are worsening or improving.","why":"Worsening losses with no revenue growth signals a death spiral. Improving losses signal a potential turnaround.","interpretation":{"high":"Losses >$100K/day and worsening.","moderate":"Losses $10-100K/day.","low":"Modest loss improvement detected."},"frequency":"Daily. Typically 15-30 earnings signals per scan.","example":"Protocol B: earnings deeply negative at -$82K/day and worsening (+15% losses in 30d).","audiences":["vc","institution"]},{"slug":"usage-price-mismatch","name":"Usage-Price Mismatch","category":"Protocol Fundamentals","category_slug":"fundamentals","what":"Detects divergence between user growth and price movement.","why":"Users growing while price falls suggests undervaluation. Price rising without users suggests fragile speculative premium.","interpretation":{"high":"Users and price diverging >40%.","moderate":"Divergence 20-40%.","low":"Mild divergence detected."},"frequency":"Daily. Typically 10-20 mismatch signals per scan.","example":"Protocol C: active users +28% but price -14% over 30d.","audiences":["trader","vc"]},{"slug":"capital-efficiency","name":"Capital Efficiency","category":"Protocol Fundamentals","category_slug":"fundamentals","what":"Compares fee/revenue growth against TVL growth to identify improving or deteriorating capital efficiency.","why":"TVL alone is misleading. Capital efficiency reveals whether locked capital is actually productive.","interpretation":{"high":"Fee growth outpacing TVL by >50%.","moderate":"Meaningful divergence between fee and TVL trends.","low":"Mild efficiency shift detected."},"frequency":"Daily. Typically 10-20 efficiency signals per scan.","example":"Protocol D: fees +47% while TVL +8% over 30d.","audiences":["vc","institution"]},{"slug":"treasury-health","name":"Treasury Health","category":"Protocol Fundamentals","category_slug":"fundamentals","what":"Analyzes protocol treasuries for concentration (>80% own tokens) and runway (non-own reserves vs operational costs).","why":"A treasury dominated by own tokens provides only circular value. Selling to fund operations crashes the price.","interpretation":{"high":"Own tokens >95% or runway <90 days.","moderate":"Own tokens 80-95% or runway 90-180 days.","low":"Treasury showing some concentration or limited runway."},"frequency":"Daily. Typically 10-25 signals per scan.","example":"Protocol E: 94% of $180M treasury is own tokens. Non-own reserves: $10.8M.","audiences":["vc","institution"]},{"slug":"governance-apathy","name":"Governance Apathy","category":"Governance Risk","category_slug":"governance","what":"Flags governance proposals with extremely low voter turnout.","why":"Low participation means decisions affecting billions in TVL are made by a handful of voters, creating governance capture risk.","interpretation":{"high":"Turnout <1% — governance is effectively unguarded.","moderate":"Turnout 1-3%.","low":"Turnout 3-5% — below healthy levels."},"frequency":"Daily. Typically 5-15 apathy signals per scan.","example":"DAO X: proposal with only 23 voters. A $500M decision made by 23 people.","audiences":["institution"]},{"slug":"controversial-proposal","name":"Controversial Proposal","category":"Governance Risk","category_slug":"governance","what":"Detects governance proposals passing with razor-thin margins (<20% vote margin).","why":"Narrow margins mean nearly half the community disagrees — creating fork risk, reversal proposals, or fragmentation.","interpretation":{"high":"Margin <5% — extremely contentious, fork risk.","moderate":"Margin 5-12% — significant division.","low":"Margin 12-20% — contested but with a working majority."},"frequency":"Daily. Typically 3-10 controversial proposals per scan.","example":"DAO Y: proposal passed with 52.3% margin (1.2M for vs 1.1M against).","audiences":["vc","institution"]},{"slug":"power-concentration","name":"Power Concentration","category":"Governance Risk","category_slug":"governance","what":"Measures governance power concentration through delegate and holder concentration metrics.","why":"When 5 holders control 60% of tokens, governance is centralized in practice despite decentralized branding.","interpretation":{"high":"Top 5 holders >70% of supply — extreme concentration.","moderate":"Top 5 holders 50-70%.","low":"Notable but less extreme concentration."},"frequency":"Daily. Typically 20-40 concentration signals per scan.","example":"Protocol F: top 5 holders own 62.4% of supply (largest: 28.1%).","audiences":["vc","institution"]},{"slug":"unlock-pressure","name":"Unlock Pressure","category":"Token Lifecycle Risk","category_slug":"token-lifecycle","what":"Identifies tokens with upcoming unlock events releasing >5% of circulating supply.","why":"Token unlocks are the most predictable supply shocks in crypto. Recipients (usually VCs/team) may sell.","interpretation":{"high":"Unlock >15% of circulating — extreme supply shock.","moderate":"Unlock 8-15% — significant supply event.","low":"Unlock 5-8% — notable but manageable."},"frequency":"Daily. Typically 10-25 unlock alerts per scan.","example":"Token G: next unlock = 45M tokens (12.3% of circulating, ~$18M) in 14 days.","audiences":["trader","vc","institution"]},{"slug":"cluster-unlock-risk","name":"Cluster Unlock Risk","category":"Token Lifecycle Risk","category_slug":"token-lifecycle","what":"Detects when multiple tokens within the same investment cluster have simultaneous upcoming unlocks.","why":"Correlated unlock timing creates compounding selling pressure that simple unlock calendars miss.","interpretation":{"high":"Combined unlock >15% across a co-invested cluster.","moderate":"Combined unlock 8-15% across cluster.","low":"Modest coordinated unlock detected."},"frequency":"Daily. Typically 2-8 cluster unlock alerts per scan.","example":"Cluster 7: 4 co-invested tokens with upcoming unlocks totaling 11.2% of circulating.","audiences":["trader","vc"]},{"slug":"exchange-liquidity-risk","name":"Exchange Liquidity Risk","category":"Token Lifecycle Risk","category_slug":"token-lifecycle","what":"Identifies tokens available on very few exchanges (1-2) or with wide bid-ask spreads (>2%).","why":"Low exchange coverage means liquidity risk and deplatforming risk. Wide spreads tax every transaction.","interpretation":{"high":"Single exchange with wide spread — severe risk.","moderate":"2 exchanges or spread >3%.","low":"Moderate exchange concentration or elevated spreads."},"frequency":"Daily. Typically 15-40 liquidity risk signals per scan.","example":"Token H: listed on only 1 exchange with $340K 24h volume. Spread 4.2%.","audiences":["trader","vc","institution"]},{"slug":"convergence-alert","name":"Convergence Alert","category":"Cross-Domain Convergence","category_slug":"convergence","what":"Detects when an entity triggers 3+ independent signal types from different analytical domains simultaneously.","why":"Individual signals can be noisy. Convergence from independent domains drops false positive probability dramatically.","interpretation":{"high":"5+ signal types converging.","moderate":"4 signal types converging.","low":"3 signal types converging."},"frequency":"Daily. Typically 30-60 convergence alerts per scan.","example":"Protocol J: 4 signal types converge — insider_flow, utilization_risk, governance_apathy, yield_anomaly.","audiences":["trader","vc","institution"]},{"slug":"narrative-synthesis","name":"Narrative Synthesis","category":"Cross-Domain Convergence","category_slug":"convergence","what":"AI-synthesized briefings connecting multiple signals into actionable context with explicit evidence chains.","why":"Raw signals require interpretation. Narrative synthesis saves hours of manual analysis and surfaces connections analysts might miss.","interpretation":{"high":"Urgent narratives — active depegs, large insider selling, governance closing within 48h.","moderate":"Watchlist narratives — developing situations.","low":"Informational narratives — context for portfolio review."},"frequency":"Daily. 15 AI-synthesized narratives per scan.","example":"HEADLINE: Lending Protocol Under Multi-Dimensional Stress. Utilization 93.2%, insiders sold $3.2M, governance vote closes in 36h.","audiences":["trader","vc","institution"]},{"slug":"watchlist-momentum","name":"Watchlist Momentum","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens with accelerating CoinGecko watchlist growth relative to their own baseline.","why":"Watchlist growth is a proxy for retail attention before it translates into buying pressure.","interpretation":{"high":"Recent watchlist growth >10% per period with 2x+ acceleration.","moderate":"Watchlist growth 3-10% outpacing baseline.","low":"Mild watchlist acceleration detected."},"frequency":"Daily. Typically 10-30 signals per scan.","example":"Token X: watchlist users grew +8.2% in latest period (142K → 153K).","audiences":["trader"]},{"slug":"sentiment-divergence","name":"Sentiment Divergence","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens where CoinGecko sentiment direction diverges from price action.","why":"Sentiment leads price at turning points. Rising sentiment with flat price suggests accumulation.","interpretation":{"high":"Sentiment shift >15pp diverging from price.","moderate":"Sentiment shift 8-15pp diverging from price.","low":"Mild sentiment-price divergence."},"frequency":"Daily. Typically 10-25 signals per scan.","example":"Token Y: bullish divergence — sentiment +12pp while price -3.2%.","audiences":["trader"]},{"slug":"social-attention-spike","name":"Social Attention Spike","category":"Social & Sentiment","category_slug":"social","what":"Identifies tokens whose watchlist growth rate is 3x+ the market-wide median.","why":"Market-relative attention is more meaningful than absolute growth.","interpretation":{"high":"Growth 10x+ above market median.","moderate":"Growth 5-10x above median.","low":"Growth 3-5x above median."},"frequency":"Daily. Typically 5-15 signals per scan.","example":"Token Z: watchlist growth +18.5%, 7.2x the market median (+2.6%).","audiences":["trader"]},{"slug":"galaxy-score-momentum","name":"Attention Health Momentum","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens with rising social-attention provider attention health significantly above the market trend.","why":"attention health captures social health holistically. Excess GS improvement signals genuine social momentum.","interpretation":{"high":"GS excess delta >20 with GS >70.","moderate":"GS excess delta 10-20.","low":"GS excess delta 5-10."},"frequency":"Daily. Typically 10-30 signals per scan.","example":"BTC: attention health rose +15 (55 → 70), excess +12 vs market median (+3).","audiences":["trader"]},{"slug":"altrank-breakout","name":"Market Rank Breakout","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens where market rank is improving sharply versus the market trend.","why":"market rank improvement means social engagement outpacing the token's market cap size.","interpretation":{"high":"market rank now in top 100 with excess improvement >200 positions.","moderate":"market rank improvement 100-200 above median.","low":"market rank improvement 50-100 above median."},"frequency":"Daily. Typically 10-25 signals per scan.","example":"LINK: market rank improved +180 positions (320 → 140), excess +150 vs market.","audiences":["trader"]},{"slug":"social-dominance-surge","name":"Social Dominance Surge","category":"Social & Sentiment","category_slug":"social","what":"Identifies tokens capturing outsized social conversation relative to market cap (3x+ ratio).","why":"Attention asymmetry precedes capital flows.","interpretation":{"high":"Social dominance 10x+ market dominance.","moderate":"Social dominance 5-10x market dominance.","low":"Social dominance 3-5x market dominance."},"frequency":"Daily. Typically 10-25 signals per scan.","example":"PEPE: social dominance 0.84% vs market dominance 0.08% (10.5x ratio).","audiences":["trader"]},{"slug":"galaxy-score-divergence","name":"Attention-Price Divergence","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens where price is rising but attention health is declining more than the market trend.","why":"Rising price with declining social health is a classic distribution signal.","interpretation":{"high":"GS dropping >15 below market trend while price up >15%.","moderate":"GS excess decline 8-15 with price up 5-15%.","low":"Mild social-price divergence."},"frequency":"Daily. Typically 5-15 signals per scan.","example":"TOKEN: attention health -18 (65 → 47) while price +12% 7d. Distribution signal.","audiences":["trader"]},{"slug":"altrank-deterioration","name":"Market Rank Deterioration","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens where price is pumping but market rank is worsening faster than the market.","why":"Price rising while social momentum fades means the rally is losing narrative foundation.","interpretation":{"high":"market rank worsening >200 above market trend with price up >10%.","moderate":"market rank excess worsening 100-200.","low":"Mild market rank deterioration with rising price."},"frequency":"Daily. Typically 5-15 signals per scan.","example":"TOKEN: market rank worsened +250 positions while price +18% 7d.","audiences":["trader"]},{"slug":"social-dominance-fade","name":"Social Dominance Fade","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens where market dominance exceeds social dominance by 2x+ — narrative is dying.","why":"After a pump, social attention fades before price corrects. Attention always leads price.","interpretation":{"high":"Market dominance 10x+ social dominance.","moderate":"Market dominance 5-10x social.","low":"Market dominance 2-5x social."},"frequency":"Daily. Typically 10-25 signals per scan.","example":"TOKEN: market share 0.12% vs social share 0.02% (6x under-discussed).","audiences":["trader"]},{"slug":"volume-price-divergence","name":"Volume-Price Divergence","category":"Social & Sentiment","category_slug":"social","what":"Detects tokens making price highs on declining volume relative to the market median.","why":"Price rising on declining volume is a textbook distribution pattern.","interpretation":{"high":"Price up >20% with volume declining >50pp below market trend.","moderate":"Price up 10-20% with volume declining 25-50pp below market.","low":"Mild volume-price divergence."},"frequency":"Daily. Typically 10-20 signals per scan.","example":"Token X: price up +15.3% but volume down -42% over 2 weeks.","audiences":["trader"]},{"slug":"momentum-exhaustion","name":"Momentum Exhaustion","category":"Social & Sentiment","category_slug":"social","what":"Detects post-spike reversals with rising volume. Token rallied >30% then drew down with increasing volume.","why":"Rising volume on falling price after a rally means sellers are distributing into remaining bids.","interpretation":{"high":"Large rally with volume surging >100% above market during decline.","moderate":"Rally reversal with volume 50-100% above market.","low":"Post-rally pullback with volume modestly above market."},"frequency":"Daily. Typically 10-30 signals per scan.","example":"Token Y: rallied +65% then -18% from peak. Volume +82% during decline.","audiences":["trader"]},{"slug":"smart-money-accumulating","name":"Smart Money Accumulating","category":"Trading Composites","category_slug":"trading","what":"Fires when 2+ independent smart money signals converge on the same entity within 72 hours.","why":"Multiple smart money signals pointing to the same token indicates informed accumulation.","interpretation":{"high":"All 3 smart money signal types converging.","moderate":"2 of 3 types converging.","low":"N/A — requires minimum 2 types."},"frequency":"Daily. Typically 5-20 entities per scan.","example":"Uniswap: smart_money_divergence + insider_flow + whale_cluster_activity.","audiences":["trader","vc"]},{"slug":"fundamentals-outpacing-price","name":"Fundamentals Outpacing Price","category":"Trading Composites","category_slug":"trading","what":"Fires when 2+ fundamental signals converge: user growth, revenue acceleration, earnings, capital efficiency.","why":"Multiple independent fundamental improvements without corresponding price action suggests undervaluation.","interpretation":{"high":"3+ fundamental signals converging.","moderate":"2 fundamental signals converging.","low":"N/A — requires minimum 2 types."},"frequency":"Daily. Typically 5-15 entities per scan.","example":"Aave: revenue_acceleration + user_growth_divergence + capital_efficiency.","audiences":["trader","vc","institution"]},{"slug":"sell-before-flood","name":"Sell Before Flood","category":"Trading Composites","category_slug":"trading","what":"Fires when upcoming unlock risk is confirmed by insider selling, smart money exit, or social deterioration.","why":"Unlocks are public info. But insiders also selling ahead of the unlock confirms the supply hit will be painful.","interpretation":{"high":"Unlock risk + insider selling + social deterioration.","moderate":"Unlock risk + one confirmation signal.","low":"N/A — requires both supply risk and confirmation."},"frequency":"Daily. Typically 2-10 entities per scan.","example":"Token Z: upcoming_unlock_risk + insider_flow (net sell) + altrank_deterioration.","audiences":["trader","vc"]},{"slug":"multi-domain-convergence","name":"Multi-Domain Convergence","category":"Trading Composites","category_slug":"trading","what":"Fires when signals from 3+ distinct analytical domains converge on the same entity within 72 hours.","why":"The highest-conviction signal — confirmed across completely independent data sources and methodologies.","interpretation":{"high":"5+ domains converging.","moderate":"4 domains converging.","low":"3 domains converging."},"frequency":"Daily. Typically 5-20 entities per scan.","example":"Protocol X: money + fundamentals + social + supply — 4 independent domains converging.","audiences":["trader","vc","institution"]},{"slug":"regime-shift-risk","name":"Regime Shift Risk","category":"Macro Regime","category_slug":"macro","what":"Composite market-wide signal combining 6 indicators: funding rates, open interest, stablecoin net flows, BTC dominance trend, cross-asset correlation, and exchange reserves. Fires when weighted score exceeds 7/10. Dynamically redistributes weights when data sources are unavailable.","why":"Entity-level signals detect protocol-specific risks but miss systemic market drawdowns. In May 2022, Nov 2022, and Aug 2024, macro signals (leverage buildup, capital flight, correlation spike) led entity-level damage by days to weeks. This signal determines whether to hold at all.","interpretation":{"high":"Score 9-10 — multiple macro indicators aligned bearishly. Reduce exposure 30-50%.","moderate":"Score 7-8 — elevated macro risk. Tighten stops, reduce new entries.","low":"Score 4-6 — some indicators firing but below signal threshold. Monitor closely."},"frequency":"Daily. At most 1 signal per scan (market-wide, not entity-specific).","example":"Regime shift risk score 8.0/10: 4/5 indicators fired — funding rate 0.08% sustained 4d, OI at 92nd percentile and rising, stablecoin outflows -$720M/week, BTC dominance +1.2pp while price flat.","audiences":["trader","vc","institution"]}],"signal_count":44}