Bankr Agent - Token Trading
This skill should be used when the user asks to "buy crypto", "sell tokens", "swap ETH", "trade on Base", "exchange tokens", "cross-chain swap", "bridge tokens", "convert ETH to WETH", or any token trading operation. Provides guidance on supported chains, amount formats, and swap operations.
- License 许可
- GPL-3.0
- 最近更新
- 2026-07-02
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- Bankr Agent - Token Trading
- version
- 1.0.0
- description
- This skill should be used when the user asks to "buy crypto", "sell tokens", "swap ETH", "trade on Base", "exchange tokens", "cross-chain swap", "bridge tokens", "convert ETH to WETH", or any token trading operation. Provides guidance on supported chains, amount formats, and swap operations.
03 SKILL.md 正文
Bankr Token Trading
Execute token trades and swaps across multiple blockchains.
Supported Chains
| Chain | Native Token |
|---|---|
| Base | ETH |
| Polygon | MATIC |
| Ethereum | ETH |
| Unichain | ETH |
| Solana | SOL |
Amount Formats
| Format | Example | Description |
|---|---|---|
| USD | $50 |
Dollar amount to spend |
| Percentage | 50% |
Percentage of your balance |
| Exact | 0.1 ETH |
Specific token amount |
Prompt Examples
Same-chain swaps:
- "Swap 0.1 ETH for USDC on Base"
- "Buy $50 of BNKR on Base"
- "Sell 50% of my ETH holdings"
Cross-chain swaps:
- "Bridge 0.5 ETH from Ethereum to Base"
- "Move 100 USDC from Polygon to Solana"
ETH/WETH conversion:
- "Convert 0.1 ETH to WETH"
- "Unwrap 0.5 WETH to ETH"
Chain Selection
- If no chain specified, Bankr selects the most appropriate chain
- Base is preferred for most operations due to low fees
- Cross-chain routes are automatically optimized
- Include chain name in prompt to specify: "Buy ETH on Polygon"
Slippage
- Default slippage tolerance is applied automatically
- For volatile tokens, Bankr adjusts slippage as needed
- If slippage is exceeded, the transaction fails safely
Common Issues
| Issue | Resolution |
|---|---|
| Insufficient balance | Reduce amount or add funds |
| Token not found | Check token symbol/address |
| High slippage | Try smaller amounts |
| Network congestion | Wait and retry |
04 同仓库更多 Skills
supermemory
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.
wolverine-strategy
WOLVERINE v2.0 — HYPE alpha hunter. Entry-only scanner, DSL-exit-only architecture. v1.1 lost -22.7% because the scanner's thesis exit chopped 25/27 trades before DSL could manage them. v2.0 removes thesis exit entirely. Scanner decides entries (score 8+, 4H/1H aligned, SM consensus). DSL manages all exits (wide Phase 1 for HYPE volatility, trailing tiers starting at +15% ROE). Leverage lowered to 7x. Max 4 entries/day. 3-hour cooldown between entries. DSL exit managed by plugin runtime via runtime.yaml.
wolf-strategy
WOLF v6.3 — Fully autonomous multi-strategy trading for Hyperliquid perps via Senpi MCP. Manages multiple strategies simultaneously, each with independent wallets, budgets, slots, and DSL configs. 5+N cron architecture: 5 shared wolf crons (Emerging Movers 3min, SM Flip 5min, Watchdog 5min, Risk Guardian 5min, Health Check 10min) plus one DSL v5.2 cron per strategy (native Hyperliquid SL sync via dsl-dynamic-stop-loss skill v5.3.1). Same asset can be traded in different strategies simultaneously. Enter early on first jumps, not at confirmed peaks. Dynamic risk-based leverage per strategy. Requires Senpi MCP connection, python3, mcporter CLI, OpenClaw cron system, and dsl-dynamic-stop-loss skill (provides dsl-cli.py + dsl-v5.py).
wolf-howl
HOWL v2 — Hunt, Optimize, Win, Learn. Nightly self-improvement loop for the WOLF autonomous trading strategy. Runs once per day (via cron) to review all trades from the last 24 hours, compute win rates, analyze signal quality correlation, evaluate DSL tier performance, identify missed opportunities, and produce concrete improvement suggestions for the wolf-strategy skill. v2 adds fee drag ratio (FDR) analysis, holding period bucketing, LONG vs SHORT regime detection, rotation cost tracking, cumulative drift detection, and gross vs net profit factor separation. Use when setting up daily trade review automation, analyzing trading performance, or improving an autonomous trading strategy through data-driven feedback loops. Requires Senpi MCP connection, mcporter CLI, and OpenClaw cron system.
whale-index
Auto-mirror top Discovery traders on Hyperliquid. Scans top 50 traders, scores on PnL rank (35%), win rate (25%), consistency (20%), hold time (10%), drawdown (10%). Creates 2-5 mirror strategies with overlap checks. Daily rebalance with 2-day watch period before swaps. Use when setting up trader mirroring, copy trading, or portfolio auto-rebalancing based on Discovery leaderboard performance.
vixen-strategy
VIXEN v1.0 — Dual-mode emerging movers scanner. Built from FOX v1.6 live trading data (+34.5% ROI). Two entry modes: STALKER (steady accumulation, score 6+, catches the SM buildup BEFORE the explosion) and STRIKER (violent FIRST_JUMP, score 9+, with raw volume confirmation to filter blow-off tops). 2-hour per-asset cooldown after Phase 1 exits. DSL High Water Mode mandatory.