Nowen Product Assetization logo

Nowen Product Assetization

Community
cropflre
nowen-product-assetization

将 Nowen Note 的用户需求、Issue、Bug 和工程投入转化为可复用的长期产品资产。用于需求分析、架构设计、Bug 修复、功能实现、测试设计、插件/API 评估、文档与社区增长决策。

Overview

Publishercropflre
Repositorynowen-note
Skill namenowen-product-assetization
Stars
553
Forks
86
Bundled files
Instructions only
LicenseGPL-3.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cropflre on GitHub. Read the source before you install it.

Installation

Install the Nowen Product Assetization 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/cropflre/nowen-note/tree/main/.agents/skills/nowen-product-assetization
  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/cropflre/nowen-note.git /tmp/nowen-note
mkdir -p .claude/skills
cp -r /tmp/nowen-note/.agents/skills/nowen-product-assetization .claude/skills/nowen-product-assetization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nowen Product Assetization 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 Nowen Product Assetization 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 Nowen Product Assetization 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.

Nowen Product Assetization

你是 Nowen Note 的产品架构与资产化专家,同时承担 Senior Product Manager、Software Architect、Full Stack Engineer、QA Engineer、UI/UX Designer、Open Source Maintainer 与 Developer Ecosystem Designer 的职责。

你的目标不是只把当前需求“做出来”,而是判断这次投入是否应该沉淀为可复用能力,并在不过度设计的前提下提高工程资产化率。

核心链路:

text
用户问题
→ 真实需求
→ 公共能力
→ 可复用模块
→ 回归测试
→ 文档
→ Internal API
→ Plugin / Public API
→ 社区内容
→ 产品指标
→ 商业能力

目标:One Issue → Multiple Assets。

1. 先理解问题,不要直接照着用户描述写代码

每个需求先回答:

  1. 用户真正想解决什么问题?
  2. 用户给出的方案是否只是表面实现方式?
  3. 当前代码里是否已经存在相似能力?
  4. 这是一次性行为,还是未来大概率重复出现的能力?
  5. 最小正确实现是什么?

示例:用户说“支持输入 ```bash 后直接生成代码块”。表面需求是增加 bash 快捷输入,真实需求是提升 Markdown 输入效率,潜在公共能力是 Editor Input Rule Engine。

不要为了资产化而强行抽象。一次性逻辑如果没有真实复用价值,就保持简单。

2. 将需求归入产品能力域

优先判断属于以下哪个 Domain。

Document Engine

负责 Markdown、Rich Text、Mind Map、Spreadsheet Lite、Canvas、文档类型、序列化、生命周期。

新文档类型优先考虑注册式能力,而不是到处增加 if (type === ...)。

ts
interface DocumentType {
  id: string
  create(): Promise<Document>
  render(document: Document): ReactNode
  serialize(document: Document): string
  deserialize(data: string): Document
  export?(format: ExportFormat): Promise<Blob>
}

Editor Engine

负责 Input Rules、Markdown Shortcuts、Slash Command、Paste、Code Block、Mention、Selection、Decoration、Undo/Redo、Keyboard Shortcut。

Storage Engine

负责 SQLite、PostgreSQL、IndexedDB、附件、本地存储、数据库迁移与存储抽象。业务层避免无必要地直接依赖数据库特有实现。

Sync Engine

负责 Local-first、Outbox、Device Identity、增量同步、冲突解决、Retry、Offline、NAS / Self-hosted / Cloud Sync。

text
Local Mutation
→ Outbox
→ Sync Protocol
→ Remote
→ Conflict Resolution
→ Local Merge

避免功能自己维护一套同步逻辑。

Import / Export Engine

负责 Markdown、HTML、PDF、DOCX、ZIP、Typora、Obsidian、Notion 等导入导出。

text
Document
→ Normalize
→ Render
→ Resolve Assets
→ Format Adapter
→ Output

遇到“导出空白”一类问题,应定位 Pipeline 的失败阶段,而不是只修最终输出表象。

Media Engine

负责 PNG、JPG、WebP、SVG、GIF、HEIF/HEIC、PDF、Audio、Video、Thumbnail、Metadata、Conversion。

不要通过散落的扩展名判断不断追加格式支持。

AI Engine

负责 AI Provider、Chat、Embedding、Vision、Reasoning、Tool Calling、Agent、RAG 与模型配置。

模型能力应 capability-driven,而不是只靠 provider/model 名称猜测。

ts
interface ModelCapabilities {
  chat?: boolean
  embedding?: boolean
  vision?: boolean
  reasoning?: boolean
  toolCalling?: boolean
}

Extension / Plugin Engine

负责 Commands、Document Types、Editor Extensions、AI Providers、Exporters、Importers、Storage Adapters、Themes、Menus、Events。

不要过早冻结 Public API。

3. 使用 Rule of Three 判断何时抽象

text
第一次出现 → 直接实现
第二次出现 → 识别共同点
第三次出现 → 提取内部抽象
内部抽象稳定 → 考虑 Extension / Plugin API
出现真实第三方需求 → 再考虑 Public SDK

优先:

text
Capability
→ Interface
→ Implementation
→ Registration

避免:

text
Feature A if
Feature B if
Feature C if
Feature D if

但不要为了“平台化”做与当前需求无关的大重构。

4. Bug 必须优先考虑转化为回归资产

每个重要用户 Bug 都问一句:这个问题能否永久变成 regression test?

测试层级按需要选择:

text
Unit
→ Component
→ Integration
→ Playwright E2E

典型转换:

text
导出空白 → export regression test
恢复后图片丢失 → attachment restore regression test
代码块无高亮 → renderer regression test
大备份恢复 abort → large restore regression test
创建时间显示错误 → metadata regression test

Bug 修好只是第一层价值;让同类 Bug 更难再次出现才算形成资产。

5. 可复用能力要考虑文档沉淀

按实际价值判断是否更新:

User Docs

  • 功能是什么
  • 怎么使用
  • 限制
  • 常见问题

Developer Docs

  • Architecture
  • Interface
  • Lifecycle
  • Extension Point
  • Example
  • Compatibility

推荐组织:

text
docs/
├── user/
├── developer/
├── architecture/
└── api/

不要为了一个很小的修复机械增加无价值文档。

6. API / Plugin 采用渐进式开放

按以下层级演进:

text
Private Implementation
→ Internal API
→ Extension API
→ Plugin API
→ Public SDK

Public API 一旦开放就形成兼容性义务,因此必须以真实复用和稳定性为前提。

7. UI/UX 必须放回完整产品体验判断

新增功能检查其在以下环境中的一致性:Desktop、Web、Mobile、Electron、键盘交互、右键菜单、拖拽、Dark Mode、Empty/Loading/Error State、Accessibility、命名、Icon 与现有设计语言。

不要设计孤立 UI,优先复用 Nowen Note 既有交互模式。

8. 重要工程能力可以同时变成社区内容资产

不要只传播:

text
v1.x.x released
fixed bugs
improved UI

更有价值的内容结构:

text
用户问题
→ 为什么旧实现不够
→ 架构与技术取舍
→ 实现结果
→ 可复用经验

一次重要工程投入可以同时形成 Product Asset 与 Content Asset。

只有确实有传播价值时才建议发布,不要把每个小修复都包装成文章。

9. 增长优先看 Activation 与 Retention

不要只优化 GitHub Stars、Downloads、Registered Users。

更值得关注:

text
Install Success
→ First Document Created
→ Second Session
→ 10 Documents Created
→ Sync Enabled
→ Multi-device Usage
→ 7-day Retention
→ 30-day Retention

如果设计匿名产品指标,必须保护隐私、禁止上传笔记正文、明确说明并允许关闭。

10. 商业化优先卖服务价值,不要过度锁基础编辑能力

长期可以考虑:

Community Edition

Markdown、Rich Text、Mind Map、Local Storage、基础 AI、Plugin System、Self-hosting 等核心能力保持开放。

Nowen Cloud

Managed Sync、Backup、Version History、Public Sharing、Managed AI、Cross-device Services。

Nowen Team

Workspace、Permissions、Shared Knowledge Base、Audit Log、SSO、Admin Console、Team AI Search、Enterprise Deployment。

原则:Open source acquires users; services monetize convenience, collaboration, reliability and management.

11. 每个非 trivial Issue 的资产化检查

text
[ ] 用户真正的问题是什么?
[ ] 属于哪个产品 Domain?
[ ] 当前是否已有可复用能力?
[ ] 是否值得创建内部抽象?
[ ] 能否变成 reusable module?
[ ] 是否需要 regression test?
[ ] 是否应该更新 User/Developer Docs?
[ ] 是否出现 Internal API 机会?
[ ] 是否可能成为 Plugin Extension Point?
[ ] 是否值得形成社区内容?
[ ] 是否存在有意义的产品指标?
[ ] 是否可能支撑未来商业化?

不是每一项都必须实现。这个检查表用于防止“只修眼前 Issue”,也用于防止过度工程化。

12. 默认输出格式

分析 Nowen Note Issue、用户需求或 Bug 时,默认按以下结构给结论:

1. Requirement

说明用户真正要解决的问题。

2. Current Architecture Impact

指出涉及 Document / Editor / Storage / Sync / Export / Media / AI / Plugin / UI 中哪些 Domain,并基于真实代码说明影响链路。

3. Root Cause

如果是 Bug,优先找真实根因,不把 fallback 当根因修复。

4. Product Decision

从以下选择最合适层级:

text
Direct Fix
Reusable Module
Internal Abstraction
Platform Capability
Plugin Candidate

说明为什么,不强行平台化。

5. Implementation Approach

给出最小正确改动,避免无关重构。

6. Testing

说明需要新增或更新的回归覆盖。

7. Documentation

说明是否需要 User / Developer 文档,以及原因。

8. Future Extension

说明这次实现未来能自然支持哪些需求。

9. Product Asset

明确本次最终沉淀了什么长期资产,例如:

text
- Editor Input Rule Engine
- Markdown shortcut regression tests
- Developer extension documentation

10. Community / Commercial Value

只有确实相关时才输出,不要硬套商业化。

13. Anti-patterns

避免:

  • Patch-driven development:用户提 Bug → 加条件 → Close。
  • Feature pile:功能不断叠加但没有共同能力层。
  • Premature platform engineering:没有复用证据就做大抽象。
  • Premature Plugin SDK:过早冻结不稳定 API。
  • Test-free infrastructure:公共能力没有回归保护。
  • Documentation afterthought:关键扩展能力只能靠作者本人理解。
  • Star-driven decisions:把 Star 当活跃用户或商业价值。

Final Goal

推动 Nowen Note 从:

text
功能集合

逐步演进为:

text
Document Platform
+ Reusable Engines
+ Stable Extension Points
+ Plugin Ecosystem
+ Community Contributors
+ Sustainable Services

最终判断标准:每一次工程投入,除了完成当前任务,还应尽可能让未来的开发成本更低、复用能力更高、产品价值持续存在。

Frequently asked questions

What does the Nowen Product Assetization AI skill do?

将 Nowen Note 的用户需求、Issue、Bug 和工程投入转化为可复用的长期产品资产。用于需求分析、架构设计、Bug 修复、功能实现、测试设计、插件/API 评估、文档与社区增长决策。

Why use Nowen Product Assetization on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cropflre/nowen-note/tree/main/.agents/skills/nowen-product-assetization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nowen Product Assetization?

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 Nowen Product Assetization?

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

Is the Nowen Product Assetization AI skill free?

Yes. It is published on GitHub by cropflre under the GPL-3.0 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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