Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
bybit-order-book
Download, process, and backtest ByBit derivatives historical order book data. Use this skill when the user wants to: (1) download historical order book snapshots from ByBit's derivatives history-data page using Selenium automation, (2) process/unzip ob500 JSONL files and filter to depth 50, (3) run any of 10 order-book-based trading strategies (Order Book Imbalance, Breakout, False Breakout, Scalping, Momentum, Reversal, Spoofing Detection, Optimal Execution, Market Making, Latency Arbitrage) against the data, or (4) generate full backtest performance reports with PnL, Sharpe ratio, win rate, max drawdown, and strategy comparison. Triggers on: "bybit order book", "order book backtest", "download bybit data", "ob500", "order book imbalance", "spoofing detection strategy", "market making backtest", "crypto order book", "depth of book backtest", "bybit historical data".
skill openclawclawhub Free
Download, process, and backtest ByBit derivatives historical order book data. Use this skill when the user wants to: (1) download historical order book snapshots from ByBit's derivatives history-data page using Selenium automation, (2) process/unzip ob500 JSONL files and filter to depth 50, (3) run any of 10 order-book-based trading strategies (Order Book Imbalance, Breakout, False Breakout, Scalping, Momentum, Reversal, Spoofing Detection, Optimal Execution, Market Making, Latency Arbitrage) against the data, or (4) generate full backtest performance reports with PnL, Sharpe ratio, win rate, max drawdown, and strategy comparison. Triggers on: "bybit order book", "order book backtest", "download bybit data", "ob500", "order book imbalance", "spoofing detection strategy", "market making backtest", "crypto order book", "depth of book backtest", "bybit historical data".
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- backtest.py, bybit_data_format.md, download_orderbook.py, process_orderbook.py, SKILL.md, strategies.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- 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.
New install
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
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.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- davidm413
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
ByBit Order Book Backtester
End-to-end pipeline: download → process → backtest → report.
Dependencies
pip install undetected-chromedriver selenium pandas numpy pyarrow --break-system-packages Chrome/Chromium must be installed for Selenium.
Workflow
The pipeline has 3 stages. Run them sequentially, or skip to later stages if data is already available.
Stage 1: Download Order Book Data
Prompt the user for: Symbol (default: BTCUSDT) Date range (default: last 30 days) Run scripts/download_orderbook.py: python scripts/download_orderbook.py \ --symbol BTCUSDT \ --start 2024-06-01 --end 2024-06-30 \ --output ./data/raw Key details: Downloads from https://www.bybit.com/derivatives/en/history-data Automatically chunks into 7-day windows (ByBit's limit) Uses undetected-chromedriver for Cloudflare bypass Outputs: ZIP files in ./data/raw/ named {date}_{symbol}_ob500.data.zip For data format details: see references/bybit_data_format.md If Selenium fails (Cloudflare blocks, UI changes): Instruct the user to manually download from the ByBit page and place ZIPs in ./data/raw/.
Stage 2: Process & Filter to Depth 50
Run scripts/process_orderbook.py: python scripts/process_orderbook.py \ --input ./data/raw \ --output ./data/processed \ --depth 50 \ --sample-interval 1s What it does: Reads JSONL from ZIPs (each line = full 500-level L2 snapshot) Filters to top 50 bid/ask levels Computes derived features: mid_price, spread, volume_imbalance, microprice Optionally downsamples (e.g., 1s, 5s, 1min) — recommended for faster backtests Outputs: Parquet files in ./data/processed/ Without downsampling: ~860K snapshots/day, ~300 MB Parquet per day per symbol. With 1s downsampling: ~86K snapshots/day, ~5 MB per day — much more practical.
Stage 3: Backtest Strategies
Run scripts/backtest.py: # Run all 10 strategies python scripts/backtest.py \ --input ./data/processed/BTCUSDT_ob50.parquet \ --output ./reports # Run specific strategies python scripts/backtest.py \ --input ./data/processed/BTCUSDT_ob50.parquet \ --strategies imbalance,breakout,market_making \ --output ./reports # Quick test with limited rows python scripts/backtest.py \ --input ./data/processed/BTCUSDT_ob50.parquet \ --max-rows 100000 \ --output ./reports Strategy keys: imbalance, breakout, false_breakout, scalping, momentum, reversal, spoofing, optimal_execution, market_making, latency_arb Outputs in ./reports/: {SYMBOL}_backtest_report.json — Full results with equity curves {SYMBOL}_backtest_report.md — Comparison table and detailed metrics Report metrics per strategy: total trades, winners/losers, win rate, cumulative PnL, Sharpe ratio, max drawdown (absolute and %), avg PnL per trade, avg hold time, profit factor, best/worst trade, equity curve. For strategy logic and tunable parameters: see references/strategies.md
Customization
To modify strategy parameters, edit the __init__ method of any strategy class in scripts/backtest.py. Each strategy's self.params dict contains all tunables. To add a new strategy: Subclass Strategy in scripts/backtest.py Implement on_snapshot(self, row, idx, df) with entry/exit logic Register in STRATEGY_MAP
Troubleshooting
Selenium can't load ByBit page: ByBit uses Cloudflare. Ensure undetected-chromedriver is up to date. Try --no-headless to debug visually. Fall back to manual download. Out of memory on processing: Use --sample-interval 1s or larger. Process one day at a time. No trades generated: Strategy thresholds may be too tight for the data period. Relax parameters (lower thresholds, shorter lookbacks) in references/strategies.md.
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs3 Scripts
- SKILL.md
- bybit_data_format.md
- strategies.md
- backtest.py
- download_orderbook.py
- process_orderbook.py