graph-thinking
Visualize complex relationships and solve problems using non-linear graph-based reasoning.
Install
mkdir -p .claude/skills/graph-thinking && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11800" && unzip -o skill.zip -d .claude/skills/graph-thinking && rm skill.zipInstalls to .claude/skills/graph-thinking
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Apply graph-based thinking to visualize complex relationships and solveKey capabilities
- →Map feature dependencies in product development
- →Analyze stakeholder relationships
- →Understand system architectures
- →Design recommendation systems or knowledge graphs
- →Identify critical bottlenecks through network analysis
- →Apply First Principles Thinking to break down problems
How it works
The skill applies graph-based thinking by identifying nodes and edges to represent concepts and their relationships. It uses principles like First Principles and Second-Order Thinking to analyze the system's topology and pathways, then documents the findings.
Inputs & outputs
When to use graph-thinking
- →Mapping feature dependencies
- →Analyzing system architecture
- →Identifying critical bottlenecks
- →Designing recommendation systems
About this skill
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
| Element | Description |
|---|---|
| Nodes | Individual elements or concepts |
| Edges | Relationships or connections between nodes |
| Clusters | Groups of highly connected nodes |
| Pathways | Routes through the network |
| Centrality | Measures identifying most important nodes |
| Topology | Structural 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:
| Sequential | Graph-Based |
|---|---|
| One path at a time | Multiple paths simultaneously |
| Linear information flow | Multi-directional exploration |
| Fixed order | Iterative refinement through loops |
| Single conclusion | Synthesized 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
| Method | Combined Use |
|---|---|
| Five Whys | Trace causal chains through the graph |
| Business Canvas | Map relationships between canvas elements |
| Jobs-to-be-Done | Connect user needs to feature nodes |
| Hypothesis Tree | Structure experiments as branching graphs |
| Stakeholder Map | Visualize 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
When not to use it
- →When the problem is simple and linear
- →When the task does not involve complex relationships or interconnected concepts
- →When the goal is to perform sequential thinking
Limitations
- →Requires visualization of relationships
- →Graphs evolve as understanding deepens
- →Avoids over-connecting unrelated elements
How it compares
This skill provides a structured, non-linear approach to problem-solving by visualizing complex relationships as graphs, which contrasts with traditional linear thought processes.
Compared to similar skills
graph-thinking side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| graph-thinking (this skill) | 0 | 3mo | No flags | Advanced |
| tech-decision | 1 | 7mo | No flags | Intermediate |
| tech-stack-evaluator | 0 | 3mo | Review | Beginner |
| ito-research | 0 | 2mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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