/install kinema-concept-research
Concept Research - Concept Status Research | 概念现状调研
- Author: LeeShunEE
- Organization: KinemaClawWorkspace
- GitHub: https://github.com/KinemaClawWorkspace/kinema-concept-research
Research whether a concept has been implemented and what it looks like. Search thoroughly and output a summary list.
调查一个概念是否已被实现、做成什么样子。彻底搜索,输出摘要清单。
Workflow | 工作流
Phase 1: Concept Clarification (Dialogue) | 阶段 1: 概念澄清(对话)
Through multi-turn dialogue clarify: | 通过多轮对话明确:
- What user wants to do | 用户想做什么
- Core functionality | 核心功能是什么
- Target users | 目标用户是谁
- Differentiation expectations | 差异化期望是什么
Output: One-sentence concept definition | 产出: 一句话概念定义
Phase 2: Keyword Breakdown | 阶段 2: 关键词拆解
Based on concept definition, break down into multiple keyword groups: | 基于概念定义,拆解为多组关键词:
- Core word variants - synonyms, near-synonyms, different expressions | 核心词变体 - 同义词、近义词、不同表述
- Tech stack words - involved technologies, frameworks, protocols | 技术栈词 - 涉及的技术、框架、协议
- Scenario words - use cases, problems to solve | 场景词 - 使用场景、解决的问题
- Combined words - core word + tech/scenario | 组合词 - 核心词 + 技术/场景
Generate Chinese and English versions for each group. | 每组生成中英文版本。
Phase 3: Broad Search | 阶段 3: 广度搜索
Search using searxng-search batch by batch: | 使用 searxng-search 逐批搜索:
- Search 1-2 pages for each keyword group | 每组关键词搜索 1-2 页结果
- Record all relevant links | 记录所有相关链接
- Preliminary relevance marking based on title/abstract | 根据标题/摘要初步标记相关性
Time filter (if search engine supports): | 时间过滤(如搜索引擎支持):
- Five years ago, two years ago, one year ago, three months ago, recent three months | 五年之前、两年之前、一年之前、三个月之前、最近三个月
Phase 4: Deep Exploration | 阶段 4: 深度探索
From high-relevance results, select 3-5 for deep exploration: | 从高相关性结果中挑选 3-5 个进行深度探索:
- Web pages: Use web_fetch to grab content | Web 页面: 使用 web_fetch 抓取内容
- GitHub Repo: Clone locally, read README | GitHub Repo: 克隆到本地,阅读 README
- PDF/Papers: Download and read | PDF/论文: 下载阅读
Record exploration content: | 探索内容记录:
- Core functionality | 核心功能
- Technical implementation | 技术实现
- Pros and cons | 优缺点
- Similarities/differences with user concept | 与用户概念的异同
Phase 5: Output Report | 阶段 5: 输出报告
Generate summary list: | 生成摘要清单:
| Field | Description | 说明 |
|---|---|---|
| Link | Original URL | 链接 |
| Overview | What it is, what it does | 概述 |
| Basic Approach | Core technical solution | 基本思路 |
| Similarities | Common points with user concept | 相同点 |
| Differences | Differences from user concept | 不同点 |
| Analysis | Opportunities, improvement space | 分析 |
Project Directory | 项目目录
All files saved in: projects/research-{uuid}/ | 所有文件保存在:projects/research-{uuid}/
projects/research-{uuid}/
├── concepts/
│ └── definition.md
├── keywords/
│ └── keywords.md
├── search/
│ ├── broad/
│ └── deep/
├── repos/
├── papers/
└── report.md
Search Tools | 搜索工具
Priority: searxng-search. If SearXNG not deployed, can use ddg-search. | 优先使用 searxng-search。如 SearXNG 未部署,可使用 ddg-search。
Related Documentation | 相关文档
- searxng-search skill
- skill-creator skill
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install kinema-concept-research - 安装完成后,直接呼叫该 Skill 的名称或使用
/kinema-concept-research触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Kinema's Concept Re-Search 是什么?
Research whether a concept has been implemented and its current state. Use multi-language keywords, multi-engine cross-validation, and multi-dimensional sear... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 184 次。
如何安装 Kinema's Concept Re-Search?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install kinema-concept-research」即可一键安装,无需额外配置。
Kinema's Concept Re-Search 是免费的吗?
是的,Kinema's Concept Re-Search 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Kinema's Concept Re-Search 支持哪些平台?
Kinema's Concept Re-Search 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Kinema's Concept Re-Search?
由 Kinema.(@leeshunee)开发并维护,当前版本 v1.0.4。