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Strategy Backtester

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shaoxing-xie
strategy-backtester

策略回测师，基于历史行情与技术指标执行轻回测编排并输出绩效评估。

Overview

Publishershaoxing-xie
Repositoryopenclaw-data-china-stock
Skill namestrategy-backtester
Stars
53
Forks
21
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by shaoxing-xie on GitHub. Read the source before you install it.

Installation

Install the Strategy Backtester AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/shaoxing-xie/openclaw-data-china-stock/tree/main/skills/strategy-backtester
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/shaoxing-xie/openclaw-data-china-stock.git /tmp/openclaw-data-china-stock
mkdir -p .claude/skills
cp -r /tmp/openclaw-data-china-stock/skills/strategy-backtester .claude/skills/strategy-backtester
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Strategy Backtester in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Strategy Backtester on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Strategy Backtester is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Strategy Backtester

目标

在无专用 tool_backtest_* 的当前能力下，基于行情与指标工具完成轻回测编排与绩效分析输出。

输入

  • 用户策略描述
  • 历史行情数据
  • 技术指标数据

输出（固定结构）

  1. 策略规格与回测窗口
  2. 收益与风险指标
  3. 交易统计与参数敏感性
  4. 限制条件与下一步实验

证据表（必选）

  • 列出 tool_fetch_market_data、tool_calculate_technical_indicators 等调用与 quality_status；收益/回撤等须来自工具或明确声明为 MVP 派生计算 并附公式。

反证与局限（必选）

  • 样本外区间、幸存者偏差、未计入成本/滑点时对结论的影响。

强制规则

  • 仅通过 manifest / tool_runner 调用依赖工具，禁止引导直连 plugins.data_collection。
  • 若缺少足够历史数据，输出 insufficient_evidence。
  • 若无专用回测工具，必须声明 MVP mode 与能力边界。
  • 禁止输出买卖点、仓位比例、杠杆建议。
  • 参数搜索范围从 config/strategy-backtester_config.yaml 读取。

依赖工具

  • tool_resolve_symbol（L2；标的解析）
  • tool_fetch_market_data
  • tool_calculate_technical_indicators
  • tool_l4_valuation_context（L4-data；标的含个股时可选并列估值事实字段）

通用输出字段

  • strategy_spec
  • backtest_window
  • performance
  • risk_metrics
  • trade_stats
  • parameter_sensitivity
  • limitations
  • next_experiments

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Strategy Backtester AI skill do?

策略回测师，基于历史行情与技术指标执行轻回测编排并输出绩效评估。

Why use Strategy Backtester on TypingMind?

Because you install it once and use it with any model. Strategy Backtester is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Strategy Backtester in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shaoxing-xie/openclaw-data-china-stock/tree/main/skills/strategy-backtester. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Strategy Backtester?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Strategy Backtester?

As many as you like. As long as a model supports skills, you can use Strategy Backtester with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Strategy Backtester AI skill free?

Yes. It is published on GitHub by shaoxing-xie under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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