wardley-mapper
Comprehensive Wardley mapping toolkit that transforms any input (structured data, unstructured text, business descriptions, technical architectures, competitive landscapes, or abstract concepts) into strategic Wardley maps. Creates visual maps showing component evolution and value chains for strategic decision-making.
$ Instalar
git clone https://github.com/pacphi/sindri /tmp/sindri && cp -r /tmp/sindri/docker/lib/extensions/vf-wardley-maps/resources ~/.claude/skills/sindri// tip: Run this command in your terminal to install the skill
name: wardley-mapper description: Comprehensive Wardley mapping toolkit that transforms any input (structured data, unstructured text, business descriptions, technical architectures, competitive landscapes, or abstract concepts) into strategic Wardley maps. Creates visual maps showing component evolution and value chains for strategic decision-making.
Wardley Mapper
Transform ANY input into a strategic Wardley map for understanding competitive positioning and evolution.
Quick Start
- Identify the scope: What system/business/concept are we mapping?
- Find the user: Who is the primary beneficiary?
- Extract components: What capabilities/activities exist?
- Determine evolution: Where does each component sit on the evolution axis?
- Map dependencies: How do components connect?
- Generate visualization: Create the map
Core Mapping Process
Step 1: User & Scope Identification
# Always start with the user need
user_need = identify_primary_user_need(input_data)
scope = define_boundary(input_data)
Key questions:
- Who is the primary user/customer?
- What need are we fulfilling?
- What is the boundary of our system?
Step 2: Component Extraction
Components can be:
- Activities: Things we do (e.g., "customer support", "data analysis")
- Practices: How we do things (e.g., "agile methodology", "DevOps")
- Data: Information assets (e.g., "customer database", "analytics")
- Knowledge: Expertise and capabilities (e.g., "ML expertise", "domain knowledge")
For different input types:
- Structured data: Extract entities, relationships, processes
- Text descriptions: Use NLP to identify nouns (components) and verbs (activities)
- Technical architectures: Map services, infrastructure, dependencies
- Business models: Extract value propositions, channels, resources
Step 3: Evolution Assessment
Use the evolution characteristics matrix:
| Stage | Genesis | Custom | Product | Commodity |
|---|---|---|---|---|
| Ubiquity | Rare | Slowly increasing | Rapidly increasing | Widespread |
| Certainty | Poorly understood | Rapid learning | Rapid learning | Known |
| Market | Undefined | Forming | Growing | Mature |
| Failures | High/unpredictable | High/reducing | Low | Very low |
| Competition | N/A | Emerging | High | Utility |
Step 4: Value Chain Positioning
Position components on Y-axis by visibility/value:
- Top (visible): User-facing, differentiating
- Middle: Supporting capabilities
- Bottom (invisible): Infrastructure, utilities
Step 5: Dependency Mapping
Connect components showing:
- Direct dependencies (solid lines)
- Data flows (dashed lines)
- Constraints (red lines)
Input Type Handlers
For Business Descriptions
See references/business-mapper.md
For Technical Systems
See references/technical-mapper.md
For Competitive Analysis
See references/competitive-mapper.md
For Data/Metrics
Map Generation
HTML/SVG Visualization
# Use scripts/generate_wardley_map.py
from scripts.generate_wardley_map import WardleyMapGenerator
generator = WardleyMapGenerator()
map_html = generator.create_map(components, dependencies)
Text-Based Map
User Need
|
+-- [Visible Component] ------------> Product (0.7)
|
+-- [Supporting Component] ---> Custom (0.4)
|
+-- [Infrastructure] --> Commodity (0.9)
Advanced Patterns
Inertia Identification
Components resisting evolution despite market forces
Gameplay Patterns
- Commoditization play: Push products to utility
- Innovation play: Create new genesis components
- Ecosystem play: Build platforms at product stage
Strategic Movements
See references/strategic-patterns.md
Validation Checklist
✓ User need clearly defined ✓ All components have evolution position ✓ Dependencies mapped ✓ No orphaned components ✓ Evolution positions justified ✓ Map tells coherent story
Output Formats
- Interactive HTML: Full visualization with tooltips
- Static SVG: For presentations/documents
- JSON Structure: For programmatic use
- Strategic Report: Analysis and recommendations
Quick Command
For instant mapping:
# Read the input and generate map immediately
exec(open('scripts/quick_map.py').read())
Quality Indicators
Good maps have:
- Clear user focus
- Logical value chains
- Justified evolution positions
- Actionable insights
- Strategic options visible
Repository
