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PilotSB
PilotSB

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Real-time oracle intelligence platform + paper prediction game

#ai #blockchain #monitoring #showdev

`DeltaScope is a real-time oracle intelligence platform + paper prediction game that monitors the gap between Pyth Network oracle prices and Hyperliquid DEX mark prices. It uses triple-source Pyth ingestion (dual Hermes WebSocket + REST polling) with Pyth Lazer ready for sub-50ms updates, an AI assistant with 6 Pyth-powered tools for querying 1,930+ price feeds, and a Predict & Win game where users bet on price direction using live Pyth oracle data — with confidence-aware settlement that refunds when oracle data is unreliable.

What It Does

Oracle prices and DEX mark prices should match — but they don't. The gap reveals liquidation risk, funding rate mechanics, and infrastructure health that most traders are blind to.

DeltaScope gives traders real-time visibility into:

  • Oracle-mark spread — Real-time discrepancy between Pyth oracle prices and Hyperliquid mark prices across 8 major assets
  • Pyth publish delay analytics — How stale is your oracle data right now? Median publish delay tracked in a 10-min rolling buffer
  • Infrastructure latency monitoring — Pyth Oracle Delay, Hyperliquid REST API latency, WebSocket delivery, and overall health score
  • Predict & Win — Paper prediction game where users predict price direction (UP/DOWN) using live Pyth prices, with alarm-based settlement, streak bonuses, and a global leaderboard
  • AI-powered analysis — Natural language queries across 1,930+ Pyth price feeds with 6 structured tools

This is the layer beneath the prices that nobody else shows.

Link

Live: https://deltascope.site

GitHub: https://github.com/0xPilotSB/deltascope

Pyth Features Used

  • ✅ Price Feeds (off-chain) — Triple-source Pyth Hermes ingestion (dual WebSocket + REST polling) with freshness dedup by publishTime
  • ✅ Price Feeds (Lazer-ready) — Pyth Pro/Lazer integration for sub-50ms updates via 3 redundant endpoints when PYTH_PRO_TOKEN is set
  • ✅ Confidence Intervals — Displayed per-asset alongside oracle prices; used in prediction settlement (refund when confidence is unreliable)
  • ✅ Historical Prices — AI chat tool queries Pyth Hermes /v2/updates/price/{timestamp} for backtesting
  • ✅ TWAP — AI chat tool queries /v2/updates/twap/latest for time-weighted average prices (1-600s windows)
  • ✅ Price Feed Search — AI tool searches 1,930+ Pyth feeds by symbol, name, or asset type via /v2/price_feeds
  • ❌ Entropy (randomness) — Not used

Features

1. Dashboard (/)

Real-time price table for 8 major assets (BTC, ETH, SOL, HYPE, ARB, DOGE, AVAX, LINK) showing:

  • Pyth oracle price vs Hyperliquid mark price side-by-side
  • Oracle discrepancy badges (color-coded by severity)
  • 24h change, annualized funding rates, open interest, 24h volume
  • Aggregate stats: total volume ($2.5B+), total OI ($4.2B+), avg funding rate
  • HIP-3 ecosystem overview (Hyperliquid's permissionless perp DEXs)

2. Ticker Analysis (/analysis)

  • Top 20 Hyperliquid leaderboard trader positions per asset
  • Long/short breakdown: counts, sizes, average entries, liquidation ranges
  • Expandable position details: leverage, unrealized PnL, margin used
  • Sort by position size, trader count, or PnL

3. Predict & Win (/predict) — NEW

Paper prediction game powered by live Pyth oracle prices:

  • Binary predictions: UP or DOWN on any of 8 assets
  • Two time windows: 1 minute (fast) and 5 minutes (standard)
  • Points economy: 1,000 starting balance, wager 10/25/50/100 per prediction
  • Alarm-based settlement: Predictions resolve automatically via Durable Object alarms against live Pyth prices
  • Streak bonuses: 3+ consecutive wins earn +10% bonus per extra win
  • Global leaderboard: Compete by points, win rate, and streaks
  • Safety mechanics: Refund on oracle unavailability or zero price movement
  • Zero real money — Validates the prediction market concept before on-chain deployment on HyperEVM

4. Latency Monitor (/latency)

Infrastructure intelligence inspired by HyperLatency:

  • Pyth Oracle Delay — Median publish delay across all tracked feeds
  • Hyperliquid REST API — Round-trip time to api.hyperliquid.xyz
  • WebSocket Delivery — Edge DO → browser delivery latency
  • Overall Health Score — Composite 0-100 score
  • Multi-line TradingView chart with 10-min rolling history (120 samples)
  • Source health table with P50/P95/MIN/MAX percentiles

5. AI Chat Assistant

Natural language queries powered by 6 structured Pyth tools:

Tool What It Does Pyth API Used
searchPriceFeeds Search 1,930+ feeds by symbol/name /v2/price_feeds
getLatestPrices Real-time prices with confidence /v2/updates/price/latest
getHistoricalPrice Price at any historical timestamp /v2/updates/price/{timestamp}
getTwap Time-weighted average (1-600s) /v2/updates/twap/latest
getHyperliquidData Cross-reference with HL perps Hyperliquid REST API
analyzePriceFeed Full analysis package Multiple endpoints combined

6. Developer API (/developers)

REST + WebSocket endpoints documented for integration:

  • GET /api/prices — Current merged Pyth + Hyperliquid state
  • GET /api/latency — Latency history + source health
  • GET /api/hip3 — HIP-3 ecosystem data
  • WS /ws/prices — Real-time stream (16ms broadcast coalescing)

Screenshots / Media

Dashboard — Real-time Oracle vs DEX Prices





Predict & Win — Paper Prediction Game

Binary UP/DOWN predictions on live Pyth prices with points economy, countdown timers, streak bonuses, and global leaderboard

Latency Monitor — Infrastructure Intelligence

Live Pyth oracle delay (1826ms Hermes → client), Hyperliquid API latency (85ms), WebSocket delivery, and overall health score with TradingView charts





AI Chat — 6 Pyth-Powered Tools

Natural language queries: "Compare BTC and ETH funding rates" → AI fetches real-time Pyth prices, queries Hyperliquid funding/OI, computes discrepancies, and presents structured analysis

Architecture

Predict & Win Settlement Flow

`plaintext
User clicks UP/DOWN → PredictionGame DO

  1. Validate wager (sufficient points)
  2. Fetch entry price from PriceAggregator DO (live Pyth price)
  3. Deduct points atomically
  4. Store prediction in SQLite
  5. Schedule DO alarm (duration + 1s)

Alarm fires → Settlement

  1. Fetch exit price from PriceAggregator DO
  2. Compare direction (up/down vs actual movement)
  3. Calculate payout (wager + streak bonus)
  4. Update points, wins/losses, streak in SQLite
  5. Reschedule alarm if more pending predictions `

Tech Stack

Framework/Language: React Router 7 (TypeScript), Vite, Tailwind CSS 4, shadcn/ui

Blockchain/Oracle: Pyth Network (Hermes WebSocket + REST + Lazer-ready), Hyperliquid L1 (WebSocket + REST)

Agent Framework: Vercel AI SDK + Cloudflare Workers AI (6 structured Pyth tools with codemode)

Deployment: Cloudflare Workers + 4 Durable Objects (edge-deployed, 24/7 uptime via DO alarms, Smart Placement)

Full Backend Stack

Component Technology Purpose
Runtime Cloudflare Workers Edge-deployed serverless runtime with Smart Placement
PriceAggregator DO Durable Object (stateful) 4 upstream connections (2× Pyth WS + 1× HL WS + 1× REST), 16ms broadcast coalescing, 24/7 alarm keep-alive
PredictionGame DO Durable Object (SQLite) Paper prediction market: users, predictions, leaderboard, alarm-based settlement
Chat DO Durable Object (AI SDK) Streaming LLM with 6 structured Pyth tools
ChatSessionsDO Durable Object (SQLite) Session index per anonymous user
Oracle Ingestion Pyth Hermes (dual WS + REST) Triple-source freshness dedup by publishTime
Oracle Ingestion (Pro) Pyth Lazer (optional) 3 redundant WS endpoints, real_time channel, sub-50ms
DEX Data Hyperliquid API allMids WebSocket + metaAndAssetCtxs REST (3s poll)

Full Frontend Stack

Component Technology
Framework React Router 7 (SSR) with typed loaders/actions
State Zustand (WebSocket connection + tick aggregation)
Charts TradingView Lightweight Charts (candlestick + multi-line latency)
UI shadcn/ui + Tailwind CSS 4 (dark theme, responsive)
Typography Space Grotesk (self-hosted via @fontsource)
AI Chat @cloudflare/ai-chat + agents SDK (lazy-mounted popup)

Key Design Decisions

  1. Single global PriceAggregator — One DO instance holds all upstream connections. Zero coordination overhead, guaranteed consistency.

  2. 16ms broadcast coalescing — queueMicrotask() for immediate dispatch or setTimeout() for remaining window. Prevents WebSocket storm from multiple upstream sources.

  3. Incremental snapshot caching — Only dirtyAssets get JSON recomputed per broadcast. Unchanged assets reuse cached objects.

  4. 24/7 keep-alive via DO Alarms — 25-second alarm cycle keeps all upstream connections alive even with zero clients. Eliminates cold-start delays.

  5. Alarm-based prediction settlement — PredictionGame DO schedules alarms per prediction duration. Settlement fetches live prices from PriceAggregator via DO-to-DO RPC. Atomic SQLite updates prevent race conditions.

  6. Triple Pyth source — Dual Hermes WS (main + beta) + REST polling. Freshest publishTime wins per asset. ~10-15% lower oracle delay than single WS.`

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