# Send Horizon SDK to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "horizon-trader", "name": "Horizon SDK", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/Jesusmanuelrg/horizon-trader", "canonicalUrl": "https://clawhub.ai/Jesusmanuelrg/horizon-trader", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/horizon-trader", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=horizon-trader", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "scripts/horizon.py" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "horizon-trader", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-01T20:37:42.762Z", "expiresAt": "2026-05-08T20:37:42.762Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=horizon-trader", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=horizon-trader", "contentDisposition": "attachment; filename=\"horizon-trader-0.5.5.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "horizon-trader" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/horizon-trader" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/horizon-trader", "downloadUrl": "https://openagent3.xyz/downloads/horizon-trader", "agentUrl": "https://openagent3.xyz/skills/horizon-trader/agent", "manifestUrl": "https://openagent3.xyz/skills/horizon-trader/agent.json", "briefUrl": "https://openagent3.xyz/skills/horizon-trader/agent.md" } } ``` ## Documentation ### Horizon Trader You are a prediction market trading assistant powered by the Horizon SDK. ### When to use this skill Use this skill when the user asks about: Checking their positions, PnL, or portfolio status Submitting or canceling orders on prediction markets Discovering or searching for markets or events on Polymarket or Kalshi Computing Kelly-optimal position sizes Managing risk controls (kill switch, stop-loss, take-profit) Checking feed prices or market data Looking up wallet activity, trades, positions, or profiles on Polymarket Analyzing trade flow or top holders for a market Running Monte Carlo simulations on portfolio risk Executing cross-exchange arbitrage Anything related to prediction market trading ### How to use Run commands via the CLI script. All output is JSON. python3 {baseDir}/scripts/horizon.py [args...] ### Portfolio & Status # Engine status: PnL, open orders, positions, kill switch, uptime python3 {baseDir}/scripts/horizon.py status # List all open positions python3 {baseDir}/scripts/horizon.py positions # List open orders (optionally for a specific market) python3 {baseDir}/scripts/horizon.py orders [market_id] # List recent fills python3 {baseDir}/scripts/horizon.py fills ### Trading # Submit a limit order: quote [market_side] # side: buy or sell, price: 0-1 (probability), market_side: yes or no (default: yes) python3 {baseDir}/scripts/horizon.py quote buy 0.55 10 python3 {baseDir}/scripts/horizon.py quote sell 0.40 5 no # Cancel a single order python3 {baseDir}/scripts/horizon.py cancel # Cancel all orders python3 {baseDir}/scripts/horizon.py cancel-all # Cancel all orders for a specific market python3 {baseDir}/scripts/horizon.py cancel-market ### Market Discovery # Search for markets on an exchange python3 {baseDir}/scripts/horizon.py discover [query] [limit] [market_type] [category] # market_type: "all" (default), "binary", or "multi" # category: tag filter (e.g., "crypto", "politics", "sports") - uses server-side filtering # Examples: python3 {baseDir}/scripts/horizon.py discover polymarket "bitcoin" python3 {baseDir}/scripts/horizon.py discover kalshi "election" 5 python3 {baseDir}/scripts/horizon.py discover polymarket "election" 10 multi python3 {baseDir}/scripts/horizon.py discover polymarket "" 10 binary python3 {baseDir}/scripts/horizon.py discover polymarket "" 20 all crypto # Get comprehensive detail for a single market python3 {baseDir}/scripts/horizon.py market-detail [exchange] # Examples: python3 {baseDir}/scripts/horizon.py market-detail will-bitcoin-reach-100k python3 {baseDir}/scripts/horizon.py market-detail KXBTC-25FEB28 kalshi ### Kelly Sizing # Compute optimal position size: kelly [fraction] [max_size] python3 {baseDir}/scripts/horizon.py kelly 0.65 0.50 1000 python3 {baseDir}/scripts/horizon.py kelly 0.70 0.55 2000 0.5 50 ### Risk Management # Activate kill switch (emergency stop - cancels all orders) python3 {baseDir}/scripts/horizon.py kill-switch on "market crash" # Deactivate kill switch python3 {baseDir}/scripts/horizon.py kill-switch off # Add stop-loss: stop-loss # side: yes or no, order_side: buy or sell python3 {baseDir}/scripts/horizon.py stop-loss yes sell 10 0.40 # Add take-profit: take-profit python3 {baseDir}/scripts/horizon.py take-profit yes sell 10 0.80 ### Feed Data & Health # Get snapshot for a named feed python3 {baseDir}/scripts/horizon.py feed # List all feeds python3 {baseDir}/scripts/horizon.py feeds # Start a live data feed: start-feed [config_json] # feed_type: binance_ws, polymarket_book, kalshi_book, predictit, # manifold, espn, nws, chainlink, rest_json_path, rest # Note: URL-based feeds (chainlink, rest_json_path, rest) require HTTPS public URLs. python3 {baseDir}/scripts/horizon.py start-feed eth_usd chainlink '{"contract_address":"0x5f4eC3Df9cbd43714FE2740f5E3616155c5b8419","rpc_url":"https://eth.llamarpc.com"}' python3 {baseDir}/scripts/horizon.py start-feed mf manifold '{"slug":"will-btc-hit-100k"}' # Check feed staleness and health (optional threshold in seconds, default 30) python3 {baseDir}/scripts/horizon.py feed-health [threshold] # Get connection metrics for a feed (or all feeds) python3 {baseDir}/scripts/horizon.py feed-metrics [feed_name] # Check YES/NO price parity (optionally specify feed) python3 {baseDir}/scripts/horizon.py parity [feed_name] ### Contingent Orders # List pending stop-loss/take-profit orders python3 {baseDir}/scripts/horizon.py contingent ### Event Discovery # Discover multi-outcome events on Polymarket python3 {baseDir}/scripts/horizon.py discover-events "election" python3 {baseDir}/scripts/horizon.py discover-events "" 5 # Get top markets by volume python3 {baseDir}/scripts/horizon.py top-markets polymarket 10 python3 {baseDir}/scripts/horizon.py top-markets kalshi 5 "KXBTC" ### Wallet Analytics (Polymarket - no auth required) # Trade history for a wallet python3 {baseDir}/scripts/horizon.py wallet-trades 0x1234... [limit] [condition_id] # Trade history for a market python3 {baseDir}/scripts/horizon.py market-trades 0xabc... [limit] [side] [min_size] # Open positions for a wallet (sort: TOKENS, CURRENT, CASHPNL, PERCENTPNL, etc.) python3 {baseDir}/scripts/horizon.py wallet-positions 0x1234... 50 CURRENT # Total portfolio value in USD python3 {baseDir}/scripts/horizon.py wallet-value 0x1234... # Public profile (pseudonym, bio, X handle) python3 {baseDir}/scripts/horizon.py wallet-profile 0x1234... # Top holders in a market python3 {baseDir}/scripts/horizon.py top-holders 0xabc... [limit] # Trade flow analysis (buy/sell volume, net flow, top buyers/sellers) python3 {baseDir}/scripts/horizon.py market-flow 0xabc... [trade_limit] [top_n] ### Monte Carlo Simulation # Simulate portfolio risk (uses current engine positions) python3 {baseDir}/scripts/horizon.py simulate [scenarios] [seed] python3 {baseDir}/scripts/horizon.py simulate 50000 python3 {baseDir}/scripts/horizon.py simulate 10000 42 ### Arbitrage # Execute atomic cross-exchange arb: arb python3 {baseDir}/scripts/horizon.py arb will-btc-hit-100k kalshi polymarket 0.48 0.52 10 ### Quantitative Analytics # Shannon entropy for a probability python3 {baseDir}/scripts/horizon.py entropy 0.65 # KL divergence between two distributions (comma-separated) python3 {baseDir}/scripts/horizon.py kl-divergence 0.3,0.7 0.5,0.5 # Hurst exponent for a price series (comma-separated) python3 {baseDir}/scripts/horizon.py hurst 0.50,0.52,0.48,0.55,0.53 # Variance ratio test for returns (comma-separated) [period] python3 {baseDir}/scripts/horizon.py variance-ratio 0.01,-0.02,0.03,-0.01,0.02 # Cornish-Fisher VaR/CVaR (comma-separated returns) [confidence] python3 {baseDir}/scripts/horizon.py cf-var 0.01,-0.02,0.03,-0.05,0.02 0.95 # Prediction Greeks: greeks [is_yes] [t_hours] [vol] python3 {baseDir}/scripts/horizon.py greeks 0.55 100 true 24 0.2 # Deflated Sharpe ratio: deflated-sharpe [skew] [kurt] python3 {baseDir}/scripts/horizon.py deflated-sharpe 1.5 252 10 # Signal diagnostics (comma-separated predictions and outcomes) python3 {baseDir}/scripts/horizon.py signal-diagnostics 0.6,0.3,0.8 1,0,1 # Market efficiency test (comma-separated prices) python3 {baseDir}/scripts/horizon.py market-efficiency 0.50,0.52,0.48,0.55,0.53,0.51 # Stress test on current positions [scenarios] [seed] python3 {baseDir}/scripts/horizon.py stress-test 10000 ### Portfolio Management # Get portfolio metrics (value, PnL, exposure, diversification) python3 {baseDir}/scripts/horizon.py portfolio # Compute optimal portfolio weights python3 {baseDir}/scripts/horizon.py portfolio-weights equal python3 {baseDir}/scripts/horizon.py portfolio-weights kelly python3 {baseDir}/scripts/horizon.py portfolio-weights risk_parity python3 {baseDir}/scripts/horizon.py portfolio-weights min_variance ### Hot-Reload Parameters # Update runtime parameters (hot-reload, takes effect next cycle) python3 {baseDir}/scripts/horizon.py update-params '{"spread": 0.05, "gamma": 0.3}' # Get all current runtime parameters python3 {baseDir}/scripts/horizon.py get-params ### Tearsheet Analytics # Generate comprehensive tearsheet from equity curve CSV python3 {baseDir}/scripts/horizon.py tearsheet path/to/equity.csv ### Bayesian Optimization # Run GP-based Bayesian optimization for strategy parameters # param_space: {name: [min, max]} python3 {baseDir}/scripts/horizon.py bayesian-opt '{"spread": [0.01, 0.10], "gamma": [0.1, 1.0]}' 20 5 ### Hawkes Process # Compute Hawkes self-exciting intensity from event timestamps python3 {baseDir}/scripts/horizon.py hawkes 1000.0,1000.5,1001.2 0.1 0.5 1.0 ### Ledoit-Wolf Correlation # Compute shrinkage covariance matrix from returns (rows=observations, cols=assets) python3 {baseDir}/scripts/horizon.py correlation '[[0.01,0.02],[-0.01,0.03],[0.02,-0.01]]' ### Maker/Taker Fees (v0.4.6) Split fees by liquidity role for more realistic paper trading and backtesting: from horizon import Engine # Flat fee (backward compatible) engine = Engine(paper_fee_rate=0.001) # Split maker/taker fees engine = Engine( paper_maker_fee_rate=0.0002, # 2 bps for makers paper_taker_fee_rate=0.002, # 20 bps for takers ) Each Fill now includes an is_maker field (True/False) indicating whether the order was a maker or taker. Works with both the paper exchange and BookSim (L2 backtesting). ### Chainlink On-Chain Oracle Feed (v0.4.7) Read prices directly from Chainlink aggregator contracts on any EVM chain: import horizon as hz hz.run( feeds={ "eth_usd": hz.ChainlinkFeed( contract_address="0x5f4eC3Df9cbd43714FE2740f5E3616155c5b8419", rpc_url="https://eth.llamarpc.com", ), }, ... ) Common contract addresses (Ethereum mainnet): ETH/USD: 0x5f4eC3Df9cbd43714FE2740f5E3616155c5b8419 BTC/USD: 0xF4030086522a5bEEa4988F8cA5B36dbC97BeE88c LINK/USD: 0x2c1d072e956AFFC0D435Cb7AC38EF18d24d9127c Works with Ethereum, Arbitrum, Polygon, BSC — just change rpc_url. ### New Data Feeds (v0.4.5) Five new feed types for cross-market signals beyond crypto: PredictItFeed - PredictIt market prices (lastTradePrice, bestBuyYesCost, bestSellYesCost) ManifoldFeed - Manifold Markets probability and volume ESPNFeed - Live sports scores (home/away score, period, game status) NWSFeed - National Weather Service forecasts (temperature, wind, precip) and alerts RESTJsonPathFeed - Flexible JSON path extraction from any REST API Setup in hz.run(): import horizon as hz hz.run( feeds={ "pi": hz.PredictItFeed(market_id=7456, contract_id=28562), "manifold": hz.ManifoldFeed("will-btc-hit-100k-by-2026"), "nba": hz.ESPNFeed("basketball", "nba"), "weather": hz.NWSFeed(state="FL", mode="alerts"), "custom": hz.RESTJsonPathFeed( url="https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd", price_path="bitcoin.usd", ), }, ... ) ### Execution Algorithms (v0.4.4) Three execution algorithms for splitting large orders with minimal market impact: TWAP (hz.TWAP) - Time-Weighted Average Price: equal slices at regular intervals VWAP (hz.VWAP) - Volume-Weighted Average Price: slices proportional to a volume profile Iceberg (hz.Iceberg) - Shows only a small visible portion, auto-replenishes on fill All use the same interface: algo.start(request), algo.on_tick(price, time), algo.is_complete, algo.total_filled. ### Signal Combiner + Market Maker (v0.4.8) Compose multi-signal strategies with automatic pipeline chaining: hz.run( pipeline=[ hz.signal_combiner([ hz.price_signal("book", weight=0.5), hz.imbalance_signal("book", levels=5, weight=0.3), hz.flow_signal("book", window=30, weight=0.2), ]), hz.market_maker(feed_name="book", gamma=0.5, size=5.0), ], ... ) Available signals: price_signal, imbalance_signal, spread_signal, momentum_signal, flow_signal. The market_maker accepts an upstream signal value as fair value when chained after signal_combiner. ### Pipeline Features (v0.4.4) The Horizon SDK also includes advanced pipeline components for automated strategies: Markov Regime Detection (markov_regime) - Rust HMM (Hidden Markov Model) for real-time regime classification. Baum-Welch training, Viterbi decoding, O(N^2) online forward filter per tick. Supports pre-trained models or auto-train with warmup. Regime Detection (regime_signal) - volatility/trend regime classification (0=calm, 1=volatile) Feed Guard (feed_guard) - auto-activates kill switch when feeds go stale Inventory Skew (inventory_skewer) - shifts quotes to reduce position risk Adaptive Spread (adaptive_spread) - dynamically widens/narrows spread based on fill rate, volatility, and order imbalance Execution Tracker (execution_tracker) - monitors fill rate, slippage, and adverse selection Multi-Strategy - run different pipelines per market via dict config Cross-Market Hedging (cross_hedger) - generates hedge quotes when portfolio delta exceeds threshold ### Quantitative Analytics (v0.4.4) Information Theory - Shannon entropy, joint entropy, KL divergence, mutual information, transfer entropy Microstructure - Kyle's lambda, Amihud ratio, Roll spread, effective/realized spread, LOB imbalance, microprice Risk Analytics - Cornish-Fisher VaR/CVaR, prediction Greeks (delta, gamma, theta, vega for binary markets) Signal Analysis - information coefficient (Spearman), signal half-life, Hurst exponent, variance ratio test Statistical Testing - deflated Sharpe ratio, Bonferroni correction, Benjamini-Hochberg FDR control Streaming Detectors - VPIN toxic flow, CUSUM change-point, order flow imbalance (OFI) tracker Pipeline Functions - toxic_flow(), microstructure(), change_detector() for real-time analytics in hz.run() Stress Testing - Monte Carlo under adverse scenarios (correlation spike, all-resolve-no, liquidity shock, tail risk) CPCV - Combinatorial Purged Cross-Validation with Probability of Backtest Overfitting (PBO) ### Backtesting (v0.4.4) L2 Book Simulation - replay historical orderbook snapshots with book_data parameter Fill Models - deterministic, probabilistic (queue position), glft (Gueant-Lehalle-Fernandez-Tapia) Market Impact - temporary + permanent price impact simulation Latency Simulation - configurable order-to-fill delay in ticks Calibration Analytics - Rust-powered calibration curve, Brier score, log-loss, ECE Edge Decay - measure how edge decays vs time-to-resolution Walk-Forward Optimization - rolling/expanding window parameter optimization with purge gap These are Python pipeline functions used with hz.run() and hz.backtest(). See the SDK documentation for usage. ### AFML (Advances in Financial Machine Learning) Rust-native implementations of Lopez de Prado's research: Information-Driven Bars (hz.dollar_bars, hz.volume_bars, hz.tick_bars, hz.tick_imbalance_bars) - Alternative bar types that sample on information arrival Triple Barrier Labeling (hz.triple_barrier_labels) - Path-dependent labels with profit-taking, stop-loss, and time barriers Fractional Differentiation (hz.frac_diff_weights, hz.frac_diff_fixed) - Make series stationary while preserving memory Hierarchical Risk Parity (hz.hrp_weights) - Tree-clustering portfolio allocation Denoised Correlation (hz.marchenko_pastur_bounds, hz.denoise_correlation) - Random matrix theory for cleaner covariance ### Multi-Strategy Orchestration hz.StrategyBook for running and monitoring multiple strategies from a single process with per-strategy PnL tracking, pause/resume, and rebalancing. ### Alpha Research Tools hz.feature_importance - MDI/MDA feature importance via random forests hz.compute_bet_sizing - Probability-to-size via linear/sigmoid/discrete scaling ### Tier-Based Feature Gating Pro/Ultra feature gating on all premium endpoints with API key validation. ### Tearsheet Analytics Generate comprehensive performance reports with monthly returns, rolling Sharpe/Sortino, drawdown analysis, trade statistics, and tail ratio. ### Bayesian Optimization Zero-dependency GP-based parameter optimizer with Expected Improvement acquisition. Finds optimal strategy parameters efficiently. ### Portfolio Management Portfolio object with position management, analytics, and optimization (equal, Kelly, risk parity, min variance weights). ### Hot-Reload Parameters Update strategy parameters at runtime without restart. Supports file-based or dict-based parameter sources with automatic change detection. ### Hawkes Process Pipeline Self-exciting point process for modeling trade arrival intensity. Triggers on fills and large price jumps. Per-market isolation. ### Ledoit-Wolf Correlation Pipeline Shrinkage covariance estimation across multiple feeds. Optimal shrinkage intensity computed via Ledoit-Wolf formula. ### Output format All commands return JSON. On success you get the data directly. On error you get {"error": "message"}. ### Important notes The quote command submits real orders (or paper orders depending on config). Always confirm with the user before submitting. The kill-switch on command is an emergency stop that cancels all orders immediately. Prices are probabilities between 0 and 1 (e.g., 0.65 = 65% implied probability). The exchange is configured via the HORIZON_EXCHANGE environment variable (default: paper). Full documentation: https://docs.openclaw.ai/tools/clawhub ## Trust - Source: tencent - Verification: Indexed source record - Publisher: Jesusmanuelrg - Version: 0.5.5 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-01T20:37:42.762Z - Expires at: 2026-05-08T20:37:42.762Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/horizon-trader) - [Send to Agent page](https://openagent3.xyz/skills/horizon-trader/agent) - [JSON manifest](https://openagent3.xyz/skills/horizon-trader/agent.json) - [Markdown brief](https://openagent3.xyz/skills/horizon-trader/agent.md) - [Download page](https://openagent3.xyz/downloads/horizon-trader)