Research Product logo

Research Product

OrganizationPopular
tsingyuai
research-product

渐进式研究当前产品，并把已经稳定、可追溯的产品认知增量写入根目录 SOUL.md。首次接入产品代码、原型或线上 URL，需要确认产品形态与已有能力，或某个增长 loop 在执行中发现新的产品事实、用户场景、问题与价值证据时使用。不得一次性臆造完整产品画像，也不得仅凭代码功能推断用户、问题或价值。

Overview

Publishertsingyuai
Repositorygrowth-lab
Skill nameresearch-product
Stars
2K
Forks
170
Bundled files
2
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • 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 tsingyuai on GitHub. Read the source before you install it.

Installation

Install the Research Product 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.
  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/tsingyuai/growth-lab.git /tmp/growth-lab
mkdir -p .claude/skills
cp -r /tmp/growth-lab/collectors/research-product .claude/skills/research-product
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Product 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 Research Product 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 Research Product 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.

渐进式产品研究

目标不是完成一份产品报告，而是让 Agent 在真实执行中逐步认识产品。每次只研究当前任务需要的部分，并更新能够跨轮次复用的稳定认知。

证据层级

按以下顺序区分，不得混写：

  1. 已观察事实：代码、配置、路由、界面、公开页面、真实数据或用户明确陈述直接支持。
  2. 暂定解释：多条事实共同支持，但仍需要使用或市场证据验证。
  3. 工作假设：为了推进当前 loop 提出的可能用户、问题、场景或价值，必须写明验证方式。
  4. 未知：没有证据时保留“未知”，不为了填满 SOUL 而补齐。

代码通常只能直接证明产品形态、组成和可见能力。不得从“存在某功能”直接推断“用户最需要它”“它解决了某个核心问题”或“这是产品差异化”。

每次执行

  1. 读取现有 SOUL.md 和当前 Model 的相关 Memory，确定这次真正缺少哪一小块产品认知。
  2. 定位产品载体：当前/相邻本地仓库、用户指定路径、原型、线上 URL 或用户描述。
  3. 只读检查与问题直接相关的代码、文档、路由、配置和页面，不进行无目标的全仓扫描。
  4. 需要验证可见行为时，让调用方 Model 使用 screenshot-assets 获取真实页面证据；截图和本次研究记录进入该 Model 的 Memory。
  5. 列出“新增事实 / 被修正事实 / 新假设 / 仍未知”，每项附来源路径、URL、截图或用户陈述。
  6. 按 SOUL 增量写入协议 修改 SOUL.md。只更新本轮有新证据的字段，不重写整份文件。
  7. 将带时间的检查过程、证据清单和下一步验证动作写入调用方 Model 的 memory/<model-name>/products/<product-slug>/。

写入边界

  • SOUL.md：产品的稳定认知、明确假设、关键未知和证据链接。
  • Model Memory：本轮检查过程、截图、页面状态、临时分析、冲突证据和后续验证任务。
  • 产品仓库：产品实现本身；除非用户要求修改，不因研究而写入。
  • Collector：只维护研究方法，不保存某个产品的事实。

发现冲突时保留旧说法和新证据，先降级为“待验证”，不要静默覆盖。用户明确纠正产品事实时，记录为用户陈述，并在能验证时补上产品证据。

交付

报告本轮实际研究了什么、SOUL 哪些行发生变化、哪些结论仍只是工作假设、证据保存在哪里，以及下一次应在什么真实行动中验证。不要宣称已经“完整理解产品”。

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 Research Product AI skill do?

渐进式研究当前产品，并把已经稳定、可追溯的产品认知增量写入根目录 SOUL.md。首次接入产品代码、原型或线上 URL，需要确认产品形态与已有能力，或某个增长 loop 在执行中发现新的产品事实、用户场景、问题与价值证据时使用。不得一次性臆造完整产品画像，也不得仅凭代码功能推断用户、问题或价值。

Why use Research Product on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tsingyuai/growth-lab/tree/main/collectors/research-product. 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 Research Product?

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 Research Product?

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

Is the Research Product AI skill free?

Yes. It is published on GitHub by tsingyuai under the Apache-2.0 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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