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pm-agent-strategy-authoring

Turn an LLM- or tool-driven idea into AgentStrategy code and evaluate it with paper trading.

Star
566
分类
营销与商业
许可证
Apache-2.0
最近提交
2026年10月12日

skills/pm-agent-strategy-authoring/SKILL.md

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PM Agent Strategy Authoring

Use this skill when the user asks for a strategy that makes decisions with an LLM, MCP tools or external APIs.

Goals

  • A runnable strategy class (an AgentStrategy subclass).
  • strategy validate and paper run both succeed.
  • No parameter grid search: agent strategies cannot be auto-tuned.

Code entry points

  • Base class contract: oracle3/strategy/agent_strategy.py (AgentStrategy).
  • LLM strategy reference: oracle3/strategy/simple_strategy.py.
  • New strategies go in strategies/.

Steps

  1. Create the skeleton
  • oracle3 strategy create --output strategies/<name>.py --class-name <ClassName> --type agent
  1. Implement the strategy
  • Call the LLM, MCP tools or external APIs inside process_event.
  • Non-determinism is fine: results may differ between calls.
  • Write the LLM output into the reasoning field with self.record_decision(reasoning=...) so it can be monitored.
  • Call trader.place_order(...) to act.
  • Guard every decision with self.is_paused() to respect the control plane.
  1. Quick validation
  • oracle3 strategy validate --strategy-ref strategies/<name>.py:<ClassName> --dry-run --events 10 --json
  1. Evaluate with paper trading (the right way to evaluate agent strategies)
  • oracle3 paper run --strategy-ref strategies/<name>.py:<ClassName> --monitor
  • Watch decisions and positions with oracle3 trade status --json.
  • Take a full snapshot with oracle3 trade state --json.
  1. Intervene and adjust
  • oracle3 trade pause / oracle3 trade resume
  • Hot-swap the strategy with oracle3 trade swap --strategy-ref strategies/<new>.py:<NewClass>.

Hard rules

  • AgentStrategy subclasses cannot be used with research auto-tune --param-grid-json; it raises an error.
  • External API calls need timeouts and error handling so they never block the event loop.
  • Check self.is_paused() before every decision.
  • Never use future information (no look-ahead).
  • Keep runs reproducible: record the strategy file path, class name and command.

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