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Agent Skill · 研究检索

graph-thinking(图思维)

graph-thinking 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

graph-thinking 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 47,825。

总安装 717周安装 29GitHub Stars 239下载 225核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:graph-thinking(图思维)
来源仓库:https://github.com/flpbalada/my-opencode-config
仓库路径:skills/graph-thinking
安装命令:
npx skills add https://github.com/flpbalada/my-opencode-config --skill graph-thinking
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/flpbalada/my-opencode-config --skill graph-thinking

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

graph-thinking 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。它能帮助 Agent 搜索思维导图工具、匹配认知模型或复用分析框架。

通过 npx skills add 命令从指定仓库安装,具体用法请参考原始 README。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/graph-thinking

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/flpbalada/my-opencode-config --skill graph-thi…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

graph-thinking 怎么安装?

在终端执行 npx skills add https://github.com/flpbalada/my-opencode-config --skill graph-thinking。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

graph-thinking 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

graph-thinking 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

graph-thinking 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

graph-thinking 用的人多吗?

公开数据是累计安装 717 次,近一周安装 29 次,下载 225 次,GitHub 239 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

graph-thinking 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
graph-thinking

图思维 · 本页

717239调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Graph Thinking - Non-Linear Problem Solving

Mental model for visualizing complex relationships and connections between ideas, concepts, or data points. Evolved from Graph-of-Thought (GoT) reasoning that mirrors human cognition.

When to Use This Skill

  • Mapping feature dependencies in product development
  • Analyzing stakeholder relationships
  • Understanding system architectures
  • Exploring interconnected concepts
  • Designing recommendation systems or knowledge graphs
  • Identifying opportunity areas through network analysis

Core Concepts

Graph Elements

ElementDescription
NodesIndividual elements or concepts
EdgesRelationships or connections between nodes
ClustersGroups of highly connected nodes
PathwaysRoutes through the network
CentralityMeasures identifying most important nodes
TopologyStructural arrangement of connections

Graph-of-Thought (GoT) Reasoning

Traditional (Chain-of-Thought):
A → B → C → D → Conclusion

Graph-of-Thought:
    ┌─── B ───┐
    │         │
A ──┼─── C ───┼──→ Synthesis → Conclusion
    │         │
    └─── D ───┘
         ↑
    Feedback Loop

GoT enables:

  • Combining arbitrary thoughts into synergistic outcomes
  • Distilling networks of thoughts for clarity
  • Enhancing ideas using feedback loops
  • Non-linear exploration of solution spaces

Fundamental Principles

First Principles Thinking

Break down complex problems into fundamental truths:

Surface Level:
"We need more marketing"
    ↓
Why?
    ↓
"Not enough customers"
    ↓
Why?
    ↓
Root Truth:
"Value proposition unclear to target audience"

Second-Order Thinking

Demand deeper analysis by asking "And then what?":

Decision: Reduce prices by 20%

First-order:  More sales
Second-order: Lower margins → Less R&D budget
Third-order:  Competitors catch up → Price war
Fourth-order: Race to bottom → Industry commoditization

Non-Linear Processing

Unlike sequential thinking:

SequentialGraph-Based
One path at a timeMultiple paths simultaneously
Linear information flowMulti-directional exploration
Fixed orderIterative refinement through loops
Single conclusionSynthesized insights from multiple angles

Analysis Framework

Double Diamond Model

Apply divergent and convergent thinking cycles:

    DISCOVER          DEFINE          DEVELOP          DELIVER
   (Diverge)        (Converge)       (Diverge)       (Converge)
       /\              \/              /\              \/
      /  \            /  \            /  \            /  \
     /    \          /    \          /    \          /    \
    /      \        /      \        /      \        /      \
   /        \      /        \      /        \      /        \

   Explore         Focus on         Generate         Focus on
   problem         specific         diverse          optimal
   space           challenges       solutions        implementation

Step 1: Map the Nodes

Identify all relevant elements:

Product Launch Analysis:

Nodes:
├── Stakeholders
│   ├── Customers
│   ├── Engineering
│   ├── Marketing
│   └── Leadership
├── Features
│   ├── Core functionality
│   ├── Nice-to-haves
│   └── Technical debt
├── Constraints
│   ├── Timeline
│   ├── Budget
│   └── Resources
└── Dependencies
    ├── External APIs
    ├── Infrastructure
    └── Regulatory

Step 2: Define Relationships (Edges)

Document connections between nodes:

Edge Types:
├── Dependency:    A requires B
├── Influence:     A affects B
├── Correlation:   A and B move together
├── Conflict:      A competes with B
└── Synergy:       A enhances B

Step 3: Identify Clusters and Patterns

Find highly connected groups:

High Centrality (Critical Nodes):
├── Authentication service → 12 dependencies
├── Database layer → 8 dependencies
└── API gateway → 6 dependencies

Clusters:
├── User-facing features (tightly coupled)
├── Backend services (loosely coupled)
└── Third-party integrations (isolated)

Step 4: Analyze Pathways

Trace routes through the network:

User Journey Graph:

Landing Page
    ↓
[Sign Up] ←→ [Social Login]
    ↓
Onboarding
    ↓           ↓
Quick Start   Full Setup
    ↓           ↓
    └─────┬─────┘
          ↓
    First Value
          ↓
    ↙    ↓    ↘
Churn  Retain  Upgrade

Output Template

After completing analysis, document as:

## Graph Thinking Analysis

**Subject:** [What you're analyzing]

**Analysis Date:** [Date]

### Node Map

| Category | Nodes   | Centrality     |
| -------- | ------- | -------------- |
| [Cat 1]  | [Nodes] | [High/Med/Low] |
| [Cat 2]  | [Nodes] | [High/Med/Low] |

### Relationship Matrix

| From | To  | Relationship | Strength |
| ---- | --- | ------------ | -------- |
| [A]  | [B] | [Type]       | [1-5]    |

### Key Insights

1. **Clusters identified:** [Description]
2. **Critical paths:** [Description]
3. **Bottlenecks:** [Description]
4. **Opportunities:** [Description]

### Recommendations

| Priority | Action   | Rationale |
| -------- | -------- | --------- |
| High     | [Action] | [Why]     |
| Medium   | [Action] | [Why]     |

Application Examples

Feature Dependency Mapping

Feature: Real-time Collaboration

Dependencies:
├── WebSocket infrastructure
│   ├── Connection management
│   └── Message queuing
├── Conflict resolution
│   ├── Operational transforms
│   └── CRDT implementation
├── Presence indicators
│   └── User state sync
└── Permissions
    ├── Document access
    └── Cursor visibility

Stakeholder Analysis

                    HIGH INFLUENCE
                          │
    Keep Satisfied        │        Manage Closely
    ┌─────────────────────┼─────────────────────┐
    │                     │                     │
    │   Executives        │    Product Owner    │
    │   Compliance        │    Key Customers    │
    │                     │                     │
LOW ──────────────────────┼────────────────────── HIGH
INTEREST                  │                      INTEREST
    │                     │                     │
    │   General Users     │    Power Users      │
    │   IT Support        │    Dev Team         │
    │                     │                     │
    └─────────────────────┼─────────────────────┘
    Monitor               │        Keep Informed
                          │
                   LOW INFLUENCE

System Architecture Analysis

Microservice Graph:

API Gateway [Centrality: 0.95]
    │
    ├── Auth Service [0.82]
    │   └── User DB
    │
    ├── Product Service [0.71]
    │   ├── Catalog DB
    │   └── Search Index
    │
    ├── Order Service [0.68]
    │   ├── Order DB
    │   └── Payment Gateway (external)
    │
    └── Notification Service [0.45]
        └── Email Provider (external)

Critical Path: Gateway → Auth → Product → Order
Bottleneck: Auth Service (single point of failure)

Best Practices

Do

  • Visualize relationships - Draw the graph, don't just describe it
  • Iterate continuously - Graphs evolve as understanding deepens
  • Measure centrality - Identify the most critical nodes
  • Look for clusters - Natural groupings reveal system structure
  • Trace pathways - Understand how information/value flows

Avoid

  • Over-connecting - Not everything relates to everything
  • Ignoring edge types - Different relationships have different meanings
  • Static thinking - Graphs change over time
  • Missing feedback loops - Circular dependencies are significant
  • Forgetting weights - Some relationships are stronger than others

Integration with Other Methods

MethodCombined Use
Five WhysTrace causal chains through the graph
Business CanvasMap relationships between canvas elements
Jobs-to-be-DoneConnect user needs to feature nodes
Hypothesis TreeStructure experiments as branching graphs
Stakeholder MapVisualize influence and interest relationships

Tools

Visualization

  • Mermaid - Code-based diagrams in markdown
  • Graphviz - Programmatic graph generation
  • Excalidraw - Hand-drawn style diagrams
  • Miro/FigJam - Collaborative whiteboarding

Analysis

  • Gephi - Network analysis and visualization
  • Neo4j - Graph database for complex queries
  • NetworkX - Python library for graph algorithms

Resources

平台分布

Codex

31.67%
按下载量换算71

Claude

31.03%
按下载量换算70

Cursor

17.66%
按下载量换算40

Gemini CLI

9.65%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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