Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Build and analyze a BTC 1h Up/Down trading strategy anchored to Binance BTCUSDT, applying edge thresholds, regime filters, and detailed trade validation.
Build and analyze a BTC 1h Up/Down trading strategy anchored to Binance BTCUSDT, applying edge thresholds, regime filters, and detailed trade validation.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
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.
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.
Maintain a profitable BTC 1h Up/Down strategy by anchoring decisions to Binance BTCUSDT (the resolution source) and enforcing anti-churn/risk rules.
Confirm the market type This skill is optimized for bitcoin-up-or-down-* 1h markets (Binance 1H open vs close). Compute the anchor signal (Binance) Fetch 1m closes + the 1h open for the relevant hour. Compute volatility (sigma) and time-to-expiry. Convert to fair probability for Up/Down. Trade only when there is measurable edge Enter only if edge = fair_prob - market_price exceeds a threshold. Add a directional guardrail: do not bet against the sign of the move when |z| is non-trivial. Exit using the right logic for the entry mode Model entries: exit on edge decay / model flip; hold to preclose when confidence is extreme. Mean-reversion entries: exit on reversion targets (not model-tp), with strict churn limits. Validate with logs Every suspected “nonsense trade” must be explained via: reason / entry_mode Binance-derived fair probability + z whether the correct exit block fired
All scripts are designed to be run from the OpenClaw workspace.
{baseDir}/scripts/binance_klines.py Pulls klines and prints JSON.
{baseDir}/scripts/binance_regime.py Computes ret5/ret15/slope10 + simple “stabilized” boolean.
{baseDir}/scripts/explain_fills.py Reads paperbot events.jsonl and prints a concise table for the last N fills: side/outcome/px/reason estimated fair_up + z “against trend?” flag
{baseDir}/references/strategy.md — the math model, parameters, and tuning checklist.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.