Alpha Research Recorder logo

Alpha Research Recorder

Community
GRD-Chang
alpha-research-recorder

Alpha 研究日志记录器 - 作为研究流程的数据持久化层。 核心功能: 1. 根据记录类型(session_meta/round/final_summary)引用对应的模板文件 2. 接收结构化数据并验证必填字段 3. 创建/更新 YAML 或 Markdown 日志文件 使用方式: - 调用时指定 record_type 和 session_id - 查看模板文件了解完整字段结构:templates/{record_type}.template - 传入数据合并到模板,生成最终文件

Overview

PublisherGRD-Chang
Repositoryworldquant-skill
Skill namealpha-research-recorder
Stars
87
Forks
21
Bundled files
3
Links
  • 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.

  • 3 bundled files

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

  • Open source

    Published by GRD-Chang on GitHub. Read the source before you install it.

Installation

Install the Alpha Research Recorder 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/GRD-Chang/worldquant-skill/tree/master/skills/alpha-research-recorder
  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/GRD-Chang/worldquant-skill.git /tmp/worldquant-skill
mkdir -p .claude/skills
cp -r /tmp/worldquant-skill/skills/alpha-research-recorder .claude/skills/alpha-research-recorder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alpha Research Recorder 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 Alpha Research Recorder 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 Alpha Research Recorder 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.

Alpha 研究记录器 Skill

技能定位

本技能是 Alpha 研究流程中的数据持久化层,负责将研究过程的结构化数据保存为可追溯的日志文件。

在研究流程中的地位

研究流程:
┌─────────────────┐      ┌─────────────────┐      ┌─────────────────┐
│ 知识检索/输入    │ ───▶ │  Alpha 生成/回测 │ ───▶ │   因子评估       │
│ (其他技能)       │      │  (其他技能)      │      │  (其他技能)      │
└────────┬────────┘      └────────┬────────┘      └────────┬────────┘
         │                        │                        │
         └────────────────────────┼────────────────────────┘
                                  ▼
                    ┌─────────────────────────┐
                    │  alpha-research-recorder │ ◀── 本技能
                    │  (数据持久化 + 文件管理)  │
                    └─────────────────────────┘
                                  │
                    ┌─────────────┴─────────────┐
                    ▼                           ▼
              session_metadata.yml        round_NNNN.yml
              (会话配置)                  (轮次记录)
                    │                           │
                    └─────────────┬─────────────┘
                                  ▼
                          final_summary.md
                         (最终总结报告)

记录类型

本技能支持三种独立的记录类型,按需调用,无固定顺序:

记录类型文件格式使用场景输出文件模板文件
session_metaYAML研究开始时记录配置和约束session_metadata.ymltemplates/session_metadata.yml.template
roundYAML单轮研究结束后记录完整过程round_NNNN.ymltemplates/round_NNNN.yml.template
final_summaryMarkdown研究完成后生成总结报告final_summary.mdtemplates/final_summary.md.template

调用方式:

  • ✅ 可以只调用 session_meta,不创建 round
  • ✅ 可以创建多个 round,延迟创建 final_summary
  • ✅ 可以中途补充或修改任何记录
  • ❌ 禁止跳过 session_meta 直接创建 round

参数规范

通用参数(所有记录类型共用)

参数类型必填默认值说明
record_typestring是-记录类型:"session_meta" / "round" / "final_summary"
root_dirstring否"logs/"研究日志根目录
session_idstring是-会话唯一标识,格式:YYYYMMDD_<主题>_<LLM>

数据参数(根据 record_type 引用对应模板)

每种记录类型的完整字段定义请查看对应的模板文件:

记录类型模板文件路径查看方式
session_meta./templates/session_metadata.yml.template包含注释说明哪些是必填字段
round./templates/round_NNNN.yml.template包含注释说明哪些是必填字段
final_summary./templates/final_summary.md.template包含注释说明哪些是必填字段

典型场景

场景 1:研究开始时快速创建 session_meta

技能操作:

  • 读取 templates/session_metadata.yml.template
  • 将传入数据合并到模板
  • 保留未填写的可选字段为空或注释
  • 创建 {root_dir}/{session_id}/session_metadata.yml

场景 2:研究进行中补充 session_meta

技能操作:

  • 读取已存在的 session_metadata.yml
  • 合并新数据到已有字段
  • 不覆盖已填写的内容
  • 更新文件

场景 3:创建 round 记录

步骤:

  1. 查看 templates/round_NNNN.yml.template
  2. 识别 [必填] 字段
  3. 传入数据

文件结构

{root_dir}/                        # 默认: logs/
└── {session_id}/                  # 例如: 20260108_analyst_sonnet/
    ├── session_metadata.yml       # 会话配置(可逐步完善)
    ├── round_0001.yml             # 第1轮(可逐步完善)
    ├── round_0002.yml             # 第2轮(可逐步完善)
    ├── ...                        # 更多轮次
    └── final_summary.md           # 最终总结(可选)

核心原则

1. 经济学分析优先 ⭐⭐⭐⭐⭐

以下字段在任何阶段都应优先填写(在模板中标注为 ⭐):

  • economic_analysis.hypothesis(经济学假设)
  • economic_interpretation(经济学解释)
  • economic_insights(经济学洞察)

2. 结构化优先

  • ✅ 使用 YAML 确保数据可解析
  • ✅ 避免自由文本,便于程序化提取
  • ✅ 标准化字段命名

成功标准

维度标准验证方法
可追溯性每个决策都有明确记录检查 rationale、hypothesis 字段
渐进性支持分阶段填写验证可选字段可后续补充
经济学深度核心经济学字段完整检查 3 个 economic_* 字段
可解析性YAML 可被程序提取使用 yaml.safe_load() 验证
灵活性支持按需调用验证可单独创建任意记录类型

模板文件

模板文件索引

模板文件记录类型格式行数说明
session_metadata.yml.templatesession_metaYAML~60会话配置完整模板
round_NNNN.yml.templateroundYAML~90轮次记录完整模板
final_summary.md.templatefinal_summaryMarkdown~406最终总结完整模板
README.md使用文档Markdown~447详细使用指南

查看方式:

bash
# 查看特定模板
cat templates/session_metadata.yml.template

# 或在 IDE 中打开
open templates/round_NNNN.yml.template

数据流向

其他技能 ──────▶ alpha-research-recorder ──────▶ YAML/MD 文件
(生成数据)         (引用模板 + 数据合并)            (持久化存储)
                       │
                       ▼
                  查看模板文件
             templates/{type}.template

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 Alpha Research Recorder AI skill do?

Alpha 研究日志记录器 - 作为研究流程的数据持久化层。 核心功能: 1. 根据记录类型(session_meta/round/final_summary)引用对应的模板文件 2. 接收结构化数据并验证必填字段 3. 创建/更新 YAML 或 Markdown 日志文件 使用方式: - 调用时指定 record_type 和 session_id - 查看模板文件了解完整字段结构:templates/{record_type}.template - 传入数据合并到模板,生成最终文件

Why use Alpha Research Recorder on TypingMind?

Because you install it once and use it with any model. Alpha Research Recorder 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 Alpha Research Recorder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/GRD-Chang/worldquant-skill/tree/master/skills/alpha-research-recorder. 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 Alpha Research Recorder?

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 Alpha Research Recorder?

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

Is the Alpha Research Recorder AI skill free?

It is published on GitHub by GRD-Chang. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇