base/demos/trading-agent

Create Trading Agent

Use This Skill When

• A user wants a new trading agent scaffold on Base.
• A user has a trading strategy and wants it turned into a runnable TypeScript project.
• Another agent needs a repeatable, headless way to generate a trading agent.
• An OpenClaw or ACP-style workflow needs a trading agent that can delegate to helper agents via virtuals.

Preferred Invocation

Use the normal local package workflow:

git clone https://github.com/base/demos.git
cd demos/agents/trading-agent
npm i
npm run dev

What The CLI Does

1. Collects project name, wallet, tools, LLM, runtime posture, and strategy.
2. Critiques the strategy with the selected LLM.
3. Produces a refined strategy plus initial guardrails.
4. Generates a runnable project with wallet wiring, selected tools, .env, prompts/strategy.md, and runtime files.

Treat the generated project as editable output, not a final artifact.

Decision Guide

Wallet Choice

Tool Choice

Default posture:

• Start narrow: one execution tool and one data tool is usually enough.
• Do not add virtuals unless helper-agent delegation is part of the strategy.
• For bankr or sponge, avoid CDP-only and built-in x402 tools entirely.

Runtime Posture

• test mode is live on Base mainnet with smaller recommended balances and faster cadence. It is validation mode, not simulation.
• self-updating periodically re-evaluates strategy instructions. Use it only when adaptive behavior is desired.
• Guardrails start with slippage, stop-loss, and max position size; they can be changed later in src/guardrails.ts.

Interactive Workflow

Use interactive mode when the user wants to think through the setup once:

npm run dev

The onboarding flow is:

1. Project name
2. Wallet provider
3. Tools
4. LLM provider + model
5. Test mode
6. Self-updating strategy
7. Strategy
8. Critique + refined strategy approval/edit
9. Experimental custom tools
10. Output directory

When guiding a user through this flow, explain that:

• wallet choice changes execution semantics
• tool choice changes the agent's action surface
• critique is a fast strategy review plus guardrail generation
• custom tool generation is experimental and should be used only when built-ins are insufficient

Headless Workflow For Agents

Prefer headless mode for autonomous agents, CI, or reproducible scaffold generation.

Use flags for one-off runs:

npm run dev -- --no-interactive \
  --name market-maker \
  --wallet cdp-server-wallet \
  --tools uniswap,coingecko,virtuals \
  --llm claude \
  --model claude-sonnet-4-6 \
  --strategy "Trade ETH/USDC on momentum with explicit exits and capped position sizing" \
  --test-mode true \
  --self-updating false \
  --output ./market-maker

Use --config for reproducibility or batch generation:

npm run dev -- --config ./agent.json --overwrite

Headless config rules:

• The JSON may be a single object or an array.
• Use guardrails.slippagePct, guardrails.stopLossPct, and guardrails.maxPositionPct when defaults are not acceptable.
• Use testMode, selfUpdating, and evaluationInterval when automation must fully specify runtime posture.
• Use --overwrite or --merge if the target directory may already exist.
• Headless mode still runs the critique/refinement step, so the relevant LLM API key must be available in the environment.

OpenClaw / ACP Guidance

For OpenClaw-style agents or any workflow that needs helper-agent delegation:

• Include virtuals.
• Ensure the ACP CLI is installed and accessible as acp, or set VIRTUALS_ACP_BIN.
• Treat virtuals as additive. It does not replace wallet execution; it adds delegation and marketplace/job capabilities.
• Only choose it when the user wants agent orchestration, helper-agent execution, or ACP marketplace interaction.

What To Hand Off After Generation

Tell the user to review the generated:

• .env for provider and wallet secrets
• prompts/strategy.md for strategy wording
• src/guardrails.ts for runtime risk controls
• src/tools/* for capability-specific changes

The scaffold prints the generated project path to stdout.