Agent skill

Horizon Trader

by LeoYeAI in LeoYeAI/openclaw-master-skills

v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling…

MITAuto-check passedBusiness, Finance & HR

Install Horizon Trader

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/horizon-trader .claude/skills/horizon-trader && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .claude/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/horizon-trader .agents/skills/horizon-trader && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .agents/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/horizon-trader .cursor/skills/horizon-trader && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .cursor/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/horizon-trader

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/horizon-trader .gemini/skills/horizon-trader && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .gemini/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/horizon-trader .github/skills/horizon-trader && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .github/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install LeoYeAI/openclaw-master-skills horizon-trader --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/horizon-trader .opencode/skills/horizon-trader && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "horizon-trader" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/horizon-trader into .opencode/skills/horizon-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "horizon-trader", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: horizon-trader
GitHub stars: 2.2k
Token cost: ~4.8k tokens
SKILL.md length: 987 words
Files: 3 (incl. scripts)
Skills in repo: 1,235
Repo updated: Jul 20, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling…

Business, Finance & HR work in your project
SKILL.md covers When to use this skill, How to use, Available commands and Maker/Taker Fees (v0.4.6), plus 5 more sections
Runs Python scripts from its folder; calls python3; reaches eth.llamarpc.com and api.coingecko.com

What it does

Horizon Trader is an agent skill from LeoYeAI/openclaw-master-skills. v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling, fractional differentiation, HRP, denoising), multi-strategy orchestration, alpha research, tier-gated features, and market discovery.

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `_meta.json` and `scripts/horizon.py`).

It sits in Business, Finance & HR. It works with Polymarket and Kalshi. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

Business, Finance & HR work in your project

Example prompts

“/horizon-trader”

Requirements

Python 3
A credential in HORIZON_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- eth.llamarpc.com
- api.coingecko.com
Also links to:
- docs.openclaw.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Horizon Trader loads about 4.8k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 987 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~86
When it runs · the whole SKILL.md, loaded when a task matches: ~4.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 987 words, ~4,833 tokens.

Download SKILL.mdSave it as .claude/skills/horizon-trader/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.

name: horizon-trader
description: v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling, fractional differentiation, HRP, denoising), multi-strategy orchestration, alpha research, tier-gated features, and market discovery.
version: 0.4.16
emoji: 📈

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.

bash

python3 {baseDir}/scripts/horizon.py <command> [args...]

Available commands

Portfolio & Status

bash

# 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

bash

# Submit a limit order: quote <market_id> <side> <price> <size> [market_side]
# side: buy or sell, price: 0-1 (probability), market_side: yes or no (default: yes)
python3 {baseDir}/scripts/horizon.py quote <market_id> buy 0.55 10
python3 {baseDir}/scripts/horizon.py quote <market_id> sell 0.40 5 no

# Cancel a single order
python3 {baseDir}/scripts/horizon.py cancel <order_id>

# 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_id>

Market Discovery

bash

# Search for markets on an exchange
python3 {baseDir}/scripts/horizon.py discover <exchange> [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 <slug_or_id> [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

bash

# Compute optimal position size: kelly <prob> <price> <bankroll> [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

bash

# 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 <market_id> <side> <order_side> <size> <trigger_price>
# side: yes or no, order_side: buy or sell
python3 {baseDir}/scripts/horizon.py stop-loss <market_id> yes sell 10 0.40

# Add take-profit: take-profit <market_id> <side> <order_side> <size> <trigger_price>
python3 {baseDir}/scripts/horizon.py take-profit <market_id> yes sell 10 0.80

Feed Data & Health

bash

# Get snapshot for a named feed
python3 {baseDir}/scripts/horizon.py feed <feed_name>

# List all feeds
python3 {baseDir}/scripts/horizon.py feeds

# Start a live data feed: start-feed <name> <feed_type> [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 <market_id> [feed_name]

Contingent Orders

bash

# List pending stop-loss/take-profit orders
python3 {baseDir}/scripts/horizon.py contingent

Event Discovery

bash

# 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)

bash

# 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

bash

# 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

bash

# Execute atomic cross-exchange arb: arb <market_id> <buy_exchange> <sell_exchange> <buy_price> <sell_price> <size>
python3 {baseDir}/scripts/horizon.py arb will-btc-hit-100k kalshi polymarket 0.48 0.52 10

Quantitative Analytics

bash

# 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 <price> <size> [is_yes] [t_hours] [vol]
python3 {baseDir}/scripts/horizon.py greeks 0.55 100 true 24 0.2

# Deflated Sharpe ratio: deflated-sharpe <sharpe> <n_obs> <n_trials> [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

bash

# 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

bash

# 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

bash

# Generate comprehensive tearsheet from equity curve CSV
python3 {baseDir}/scripts/horizon.py tearsheet path/to/equity.csv

Bayesian Optimization

bash

# 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

bash

# 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

bash

# 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:

python

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:

python

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():

python

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:

python

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)

Show full SKILL.md (381 more words)Show less

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.

New Features (v0.4.16)

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.

New Features (v0.4.14)

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

Files

SKILL.md and 2 other files (scripts) in skills/horizon-trader of LeoYeAI/openclaw-master-skills.

SKILL.md
_meta.json
scripts/horizon.py

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Horizon Trader next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Horizon Trader compared with similar skills
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Horizon Trader this skillLeoYeAI/openclaw-master-skills	2.2k	—	~4.8k	Automated safety check: Pass	MIT	2 mo ago
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Dr Manhattanguzus/dr-manhattan	204	—	~2k	Automated safety check: Pass	Apache-2.0	2 mo ago
Polymarket Tennislivetennisapi/livetennisapi-mcp	152	—	~3k	Automated safety check: Pass	MIT	4 days ago
Feedsalsk1992/CloddsBot	3k	—	~1.8k	Automated safety check: Pass	MIT	8 days ago
Portfolio Syncalsk1992/CloddsBot	3k	—	~3.6k	Automated safety check: Pass	MIT	8 days ago

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Questions about Horizon Trader

What does Horizon Trader do?

v0.4.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling…. Horizon Trader is an agent skill from LeoYeAI/openclaw-master-skills.16 - Trade prediction markets (Polymarket, Kalshi) - positions, orders, risk management, Kelly sizing, wallet analytics, Monte Carlo, arbitrage, quantitative analytics, AFML (bars, labeling, fractional differentiation, HRP, denoising), multi-strategy orchestration, alpha research, tier-gated features, and market discovery.

When should I use Horizon Trader?

Horizon Trader fits situations like: business, Finance & HR work in your project.

How do I install Horizon Trader in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a claude-code`. Or copy the skill folder (skills/horizon-trader in LeoYeAI/openclaw-master-skills) into .claude/skills/horizon-trader in your project. Claude Code loads it when a task matches its description.

How do I install Horizon Trader in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a codex`. Or copy the skill folder (skills/horizon-trader in LeoYeAI/openclaw-master-skills) into .agents/skills/horizon-trader in your project. Codex loads it when a task matches its description.

Can I use Horizon Trader in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill horizon-trader -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/horizon-trader, .gemini/skills/horizon-trader, .github/skills/horizon-trader and .opencode/skills/horizon-trader in your project.

What does Horizon Trader need to run?

Going by SKILL.md and its folder, Horizon Trader needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; A credential in HORIZON_API_KEY.

Does Horizon Trader access the network?

SKILL.md names 3 domains. In commands or code: eth.llamarpc.com and api.coingecko.com; the agent is likely to contact these when it follows the instructions. As links in the text: docs.openclaw.ai. This is read from the text; nothing was executed.

Is Horizon Trader safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Horizon Trader use?

Horizon Trader is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Horizon Trader use?

About 4.8k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Horizon Trader?

Skills that share tags, products or a category with Horizon Trader: Digital Oracle (komako-workshop/digital-oracle, 878 stars), Dr Manhattan (guzus/dr-manhattan, 204 stars), Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars) and Feeds (alsk1992/CloddsBot, 3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Horizon Trader?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Horizon Trader

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Horizon Trader

When to use this skill

How to use

Available commands

Portfolio & Status

Trading

Market Discovery

Kelly Sizing

Risk Management

Feed Data & Health

Contingent Orders

Event Discovery

Wallet Analytics (Polymarket - no auth required)

Monte Carlo Simulation

Arbitrage

Quantitative Analytics

Portfolio Management

Hot-Reload Parameters

Tearsheet Analytics

Bayesian Optimization

Hawkes Process

Ledoit-Wolf Correlation

Maker/Taker Fees (v0.4.6)

Chainlink On-Chain Oracle Feed (v0.4.7)

New Data Feeds (v0.4.5)

Execution Algorithms (v0.4.4)

Signal Combiner + Market Maker (v0.4.8)

Pipeline Features (v0.4.4)

Quantitative Analytics (v0.4.4)

Backtesting (v0.4.4)

New Features (v0.4.16)

AFML (Advances in Financial Machine Learning)

Multi-Strategy Orchestration

Alpha Research Tools

Tier-Based Feature Gating

New Features (v0.4.14)

Tearsheet Analytics

Bayesian Optimization

Portfolio Management

Hot-Reload Parameters

Hawkes Process Pipeline

Ledoit-Wolf Correlation Pipeline

Output format

Important notes

Files

Compare with similar skills

Similar skills

More from LeoYeAI/openclaw-master-skills

Related

Questions about Horizon Trader