# Send Crypto Self-Learning 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": "crypto-self-learning", "name": "Crypto Self-Learning", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/totaleasy/crypto-self-learning", "canonicalUrl": "https://clawhub.ai/totaleasy/crypto-self-learning", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/crypto-self-learning", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=crypto-self-learning", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "data/trades.json", "scripts/analyze.py", "scripts/generate_rules.py", "scripts/log_trade.py", "scripts/update_memory.py" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "crypto-self-learning", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T23:45:21.091Z", "expiresAt": "2026-05-07T23:45:21.091Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=crypto-self-learning", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=crypto-self-learning", "contentDisposition": "attachment; filename=\"crypto-self-learning-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "crypto-self-learning" }, "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/crypto-self-learning" }, "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/crypto-self-learning", "downloadUrl": "https://openagent3.xyz/downloads/crypto-self-learning", "agentUrl": "https://openagent3.xyz/skills/crypto-self-learning/agent", "manifestUrl": "https://openagent3.xyz/skills/crypto-self-learning/agent.json", "briefUrl": "https://openagent3.xyz/skills/crypto-self-learning/agent.md" } } ``` ## Documentation ### Crypto Self-Learning 🧠 AI-powered self-improvement system for crypto trading. Learn from every trade to increase accuracy over time. ### 🎯 Core Concept Every trade is a lesson. This skill: Logs every trade with full context Analyzes patterns in wins vs losses Generates rules from real data Updates memory automatically ### πŸ“ Log a Trade After EVERY trade (win or loss), log it: python3 {baseDir}/scripts/log_trade.py \\ --symbol BTCUSDT \\ --direction LONG \\ --entry 78000 \\ --exit 79500 \\ --pnl_percent 1.92 \\ --leverage 5 \\ --reason "RSI oversold + support bounce" \\ --indicators '{"rsi": 28, "macd": "bullish_cross", "ma_position": "above_50"}' \\ --market_context '{"btc_trend": "up", "dxy": 104.5, "russell": "up", "day": "tuesday", "hour": 14}' \\ --result WIN \\ --notes "Clean setup, followed the plan" ### Required Fields: FieldDescriptionExample--symbolTrading pairBTCUSDT--directionLONG or SHORTLONG--entryEntry price78000--exitExit price79500--pnl_percentProfit/Loss %1.92 or -2.5--resultWIN or LOSSWIN ### Optional but Recommended: FieldDescription--leverageLeverage used--reasonWhy you entered--indicatorsJSON with indicators at entry--market_contextJSON with macro conditions--notesPost-trade observations ### πŸ“Š Analyze Performance Run analysis to discover patterns: python3 {baseDir}/scripts/analyze.py Outputs: Win rate by direction (LONG vs SHORT) Win rate by day of week Win rate by RSI ranges Win rate by leverage Best/worst setups identified Suggested rules ### Analyze Specific Filters: python3 {baseDir}/scripts/analyze.py --symbol BTCUSDT python3 {baseDir}/scripts/analyze.py --direction LONG python3 {baseDir}/scripts/analyze.py --min-trades 10 ### 🧠 Generate Rules Extract actionable rules from your trade history: python3 {baseDir}/scripts/generate_rules.py This analyzes patterns and outputs rules like: 🚫 AVOID: LONG when RSI > 70 (win rate: 23%, n=13) βœ… PREFER: SHORT on Mondays (win rate: 78%, n=9) ⚠️ CAUTION: Trades with leverage > 10x (win rate: 35%, n=20) ### πŸ“ˆ Auto-Update Memory Apply learned rules to agent memory: python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md This appends a "## 🧠 Learned Rules" section with data-driven insights. ### Dry Run (preview changes): python3 {baseDir}/scripts/update_memory.py --memory-path /path/to/MEMORY.md --dry-run ### πŸ“‹ View Trade History python3 {baseDir}/scripts/log_trade.py --list python3 {baseDir}/scripts/log_trade.py --list --last 10 python3 {baseDir}/scripts/log_trade.py --stats ### πŸ”„ Weekly Review Run weekly to see progress: python3 {baseDir}/scripts/weekly_review.py Generates: This week's performance vs last week New patterns discovered Rules that worked/failed Recommendations for next week ### πŸ“ Data Storage Trades are stored in {baseDir}/data/trades.json: { "trades": [ { "id": "uuid", "timestamp": "2026-02-02T13:00:00Z", "symbol": "BTCUSDT", "direction": "LONG", "entry": 78000, "exit": 79500, "pnl_percent": 1.92, "result": "WIN", "indicators": {...}, "market_context": {...} } ] } ### 🎯 Best Practices Log EVERY trade - Wins AND losses Be honest - Don't skip bad trades Add context - More data = better patterns Review weekly - Patterns emerge over time Trust the data - If data says avoid something, AVOID IT ### πŸ”— Integration with tess-cripto Add to tess-cripto's workflow: Before trade: Check rules in MEMORY.md After trade: Log with full context Weekly: Run analysis and update memory Skill by Total Easy Software - Learn from every trade πŸ§ πŸ“ˆ ## Trust - Source: tencent - Verification: Indexed source record - Publisher: totaleasy - Version: 1.0.0 ## 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: 2026-04-30T23:45:21.091Z - Expires at: 2026-05-07T23:45:21.091Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/crypto-self-learning) - [Send to Agent page](https://openagent3.xyz/skills/crypto-self-learning/agent) - [JSON manifest](https://openagent3.xyz/skills/crypto-self-learning/agent.json) - [Markdown brief](https://openagent3.xyz/skills/crypto-self-learning/agent.md) - [Download page](https://openagent3.xyz/downloads/crypto-self-learning)