什么是 Research Matrix Builder？

Research Matrix Builder 是一款专为简化 Openclaw Skills 生态系统中学术文献综述过程而设计的精密工具。它允许研究人员通过将多样化的源材料规范化为统一架构，系统地比较各种论文或笔记中的方法、数据集、结果和研究空白。

通过利用此技能，用户可以将原始学术数据转化为结构化、可操作的见解。Research Matrix Builder 专注于识别主题集群和矛盾的发现，使其成为任何为研究和开发构建 Openclaw Skills 仓库的人员的重要组件。

下载入口:https://github.com/openclaw/skills/tree/main/skills/52yuanchangxing/research-matrix-builder

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

Research Matrix Builder 应用场景

• 为论文或期刊投稿创建全面的文献综述表格。
• 识别研究语料库中的特定研究空白和局限性。
• 将零散的研究笔记规范化为标准化的 CSV 格式以进行数据分析。
• 为系统性综述开发叙述性综合大纲。
• 快速比较多个科学摘要的方法论和指标。

1. 将论文列表、摘要或研究笔记等源材料输入系统。
2. 该技能根据预定义的矩阵架构对每个来源进行规范化。
3. 提取关键实体，如问题陈述、方法、数据、指标和局限性。
4. 对相似的方法论和矛盾的结果进行聚类，以提供主题概览。
5. 系统为用户生成结构化的文献矩阵 CSV 和详细的差距摘要。

Research Matrix Builder 配置指南

要利用此技能，请确保您的本地环境中已安装 python3，因为它是必需的依赖项。按照 Openclaw Skills 的标准集成流程将其添加到您的工作区。

# Verify your Python installation
python3 --version

# The skill relies on local scripts and resources
# Path: scripts/build_matrix.py
# Path: resources/matrix_schema.csv

Research Matrix Builder 数据架构与分类体系

该技能将研究数据组织成结构化的分类法，以确保清晰度和可重复性。以下架构用于数据提取：

所有生成的文件都存储在本地，为 Openclaw Skills 用户提供可审计的轨迹。

name: research-matrix-builder
description: Build literature matrices from papers, notes, and abstracts to compare
  methods, data, findings, and research gaps.
version: 1.1.0
metadata:
  openclaw:
    requires:
      bins:
      - python3
    emoji: ??

Research Matrix Builder

Purpose

Build literature matrices from papers, notes, and abstracts to compare methods, data, findings, and research gaps.

Trigger phrases

• 文献矩阵
• build a literature matrix
• 整理论文综述
• research gap table
• 做研究对比表

Ask for these inputs

• paper list or notes
• research question
• matrix dimensions
• citation style if needed

Workflow

1. Normalize each source into the bundled matrix schema.
2. Extract problem, method, data, metric, result, limitation, and gap.
3. Cluster similar methods and contradictory findings.
4. Generate a matrix CSV and a narrative synthesis outline.
5. Keep missing fields explicit and cite where possible.

Output contract

• literature matrix CSV
• thematic clusters
• gap summary
• review outline

Files in this skill

• Script: {baseDir}/scripts/build_matrix.py
• Resource: {baseDir}/resources/matrix_schema.csv

Operating rules

• Be concrete and action-oriented.
• Prefer preview / draft / simulation mode before destructive changes.
• If information is missing, ask only for the minimum needed to proceed.
• Never fabricate metrics, legal certainty, receipts, credentials, or evidence.
• Keep assumptions explicit.

Suggested prompts

• 文献矩阵
• build a literature matrix
• 整理论文综述

Use of script and resources

Use the bundled script when it helps the user produce a structured file, manifest, CSV, or first-pass draft. Use the resource file as the default schema, checklist, or preset when the user does not provide one.

Boundaries

• This skill supports planning, structuring, and first-pass artifacts.
• It should not claim that files were modified, messages were sent, or legal/financial decisions were finalized unless the user actually performed those actions.

Compatibility notes

• Directory-based AgentSkills/OpenClaw skill.
• Runtime dependency declared through metadata.openclaw.requires.
• Helper script is local and auditable: scripts/build_matrix.py.
• Bundled resource is local and referenced by the instructions: resources/matrix_schema.csv.