deploy-live-trading
Deploy and manage live trading agents on Hyperliquid. ⚠️ HIGH RISK - REAL CAPITAL AT STAKE ⚠️ Provides deployment_create (launch agent, $0.50), deployment_list (monitor), deployment_start/stop (control), and account tools (credit management). Supports EOA (1 deployment max) and Hyperliquid Vault (200+ USDC required, unlimited deployments). CRITICAL: NEVER deploy without thorough backtesting (6+ months, Sharpe >1.0, drawdown <20%). Start small, monitor daily, define exit criteria before deploying.
What this skill does
# Deploy Live Trading ``` ╔══════════════════════════════════════════════════════════╗ ║ ║ ║ ⚠️ LIVE TRADING RISKS REAL CAPITAL ⚠️ ║ ║ ║ ║ • You can lose ALL deployed capital ║ ║ • Bugs in strategy code cause significant losses ║ ║ • Market conditions change - backtest ≠ live ║ ║ • NEVER deploy without thorough backtesting ║ ║ • Start with small capital to validate live behavior ║ ║ • Monitor deployments actively (daily minimum) ║ ║ • Define exit criteria BEFORE deploying ║ ║ ║ ║ THIS IS NOT A SIMULATION ║ ║ REAL MONEY WILL BE TRADED ║ ║ ║ ╚══════════════════════════════════════════════════════════╝ ``` ## Quick Start This skill deploys strategies to live trading on Hyperliquid. Use ONLY after thorough backtesting and validation. **Load the tools first**: ``` Use MCPSearch to select: mcp__workbench__deployment_create Use MCPSearch to select: mcp__workbench__deployment_list Use MCPSearch to select: mcp__workbench__deployment_stop ``` **BEFORE deploying, complete this checklist**: - [ ] Backtested on 6+ months of data - [ ] Sharpe ratio >1.0, max drawdown <20% - [ ] Tested on multiple time periods - [ ] Code reviewed for bugs - [ ] Risk management validated (stop loss, position sizing) - [ ] Credit balance sufficient - [ ] Monitoring plan established - [ ] Exit criteria defined - [ ] Starting with small capital (<10% of intended final size) **If ANY item unchecked, DO NOT DEPLOY** **When to use this skill**: - After extensive backtesting shows consistent profitability - When ready to risk real capital - When you can monitor the deployment actively **When NOT to use this skill**: - Strategy not thoroughly tested (use `test-trading-strategies` first) - Haven't reviewed strategy code - Don't have monitoring plan - Can't check deployment daily for first week - Haven't defined when to stop deployment ## Available Tools (6) ### deployment_create **Purpose**: Deploy strategy to live trading on Hyperliquid **Parameters**: - `strategy_name` (required): Name of strategy to deploy - `symbol` (required): Trading pair (e.g., "BTC-USDT") - `timeframe` (required): Candle interval (1m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d) - `leverage` (optional, 1-5): Position multiplier (default: 1) - `deployment_type` (optional): "eoa" (wallet, default) or "vault" - `vault_name` (required for vault): Unique vault name - `vault_description` (optional): Vault description **Returns**: Deployment ID, status, wallet address, configuration **Pricing**: $0.50 per deployment **Constraints**: - **EOA**: Max 1 active deployment per wallet - **Vault**: Requires 200+ USDC in wallet, unlimited deployments **Use when**: All pre-deployment criteria met (see checklist) ### deployment_list **Purpose**: Monitor active deployments **Parameters**: None **Returns**: List of all deployments with status, performance, configuration **Pricing**: Free **Use when**: Checking deployment status, monitoring performance ### deployment_start **Purpose**: Resume stopped deployment **Parameters**: - `deployment_id` (required): ID of deployment to resume **Returns**: Updated deployment status **Pricing**: Free **Use when**: Restarting previously stopped deployment after validation/fixes ### deployment_stop **Purpose**: Halt live trading **Parameters**: - `deployment_id` (required): ID of deployment to stop **Returns**: Updated deployment status **Pricing**: Free **Use when**: - Live performance degrades significantly - Need to update strategy code - Market conditions change fundamentally - ANY red flag triggered (see Red Flags section) ### get_credit_balance **Purpose**: Check available USDC credits **Parameters**: None **Returns**: Current credit balance **Pricing**: Free **Use when**: Before deployment (verify sufficient credits), monitoring spending ### get_credit_transactions **Purpose**: View credit transaction history **Parameters**: None **Returns**: List of credit transactions **Pricing**: Free **Use when**: Auditing spending, tracking costs ## Core Concepts ### Deployment Types **EOA (Externally Owned Account)**: ``` Type: Direct wallet trading Setup: Immediate (no additional requirements) Limit: Max 1 active deployment per wallet Complexity: Lower Best for: Testing, personal trading, single strategy Cost: $0.50 to create Advantages: ✓ Simple setup ✓ Immediate deployment ✓ No minimum balance requirement Disadvantages: ✗ Only 1 deployment per wallet ✗ No public performance tracking ✗ Personal wallet at risk ``` **Hyperliquid Vault**: ``` Type: Professional vault setup Setup: Requires 200+ USDC in wallet Limit: Unlimited deployments Complexity: Higher Best for: Multiple strategies, professional trading, public showcasing Cost: $0.50 per deployment Advantages: ✓ Unlimited deployments ✓ Public TVL and performance tracking ✓ Professional infrastructure ✓ Separate from personal wallet Disadvantages: ✗ Requires 200+ USDC setup ✗ More complex configuration ✗ Public performance visibility ``` **Which to choose**: ``` Choose EOA if: - First deployment (testing live behavior) - Running single strategy - Want simple setup - Don't need multiple simultaneous strategies Choose Vault if: - Running multiple strategies - Want professional setup - Need public performance tracking - Trading with significant capital - Building track record ``` ### Leverage Guidelines **Understanding leverage**: ``` Leverage = Position size / Available capital 1x leverage: $1000 capital → $1000 position 2x leverage: $1000 capital → $2000 position 3x leverage: $1000 capital → $3000 position Key points: - Leverage multiplies BOTH gains AND losses - Higher leverage = higher risk - Liquidation risk increases with leverage - Start conservative (1-2x) ``` **Recommended leverage by risk profile**: ``` Conservative (1x): - No amplification - Lower returns, lower risk - Recommended for first deployments - Drawdown ≈ backtest drawdown Moderate (2-3x): - 2-3× returns and risk - Requires careful monitoring - Only after 1x deployment validated - Drawdown ≈ 2-3× backtest drawdown Aggressive (4-5x): - 4-5× returns and risk - Very risky, high liquidation chance - NOT recommended for most users - Drawdown ≈ 4-5× backtest drawdown - Can lose entire capital quickly ``` **Leverage and drawdown**: ``` Backtest: 15% max drawdown 1x deployment: 15% expected drawdown 2x deployment: 30% expected drawdown (may hit margin call) 3x deployment: 45% expected drawdown (very likely liquidation) Rule: Keep leverage low enough that backtest drawdown × leverage < 25% ``` ### Risk Management in Live Trading **Position sizing**: ``` Strategy controls position size via code (85-95% margin usage) Deployment leverage multiplies available margin Total risk = Strategy position size × Deployment leverage Example: - Capital: $1000 - Strategy uses 90% margin - Deployment leverage: 2x - Actual position: $1000 × 0.90 × 2 = $1800 Position size is LARGER than capital (risk of liquidation) ``` **Mental stop loss** (define BEFORE deploying): ``` Example thresholds: - Stop if down 10% from starting capital - Stop if down 15% from peak - Stop if drawdown >1.5× backtest max drawdown Write down your threshold: "I will stop this deployment if capital drops to $______" DO NOT move this threshold once deployed (discipline is critical) ``` **Monitoring frequency**: ``` First 24-48 hours: Check every 2-4 hours First week: Check daily minimum First month: Check every 2-3 days After 1 month: Weekly check acceptable (if performing well) NEVER: - Deploy and forget - Ignore for >1 week during first month - Assume backtest = live performance ```
Related in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.