C4 Context

[One-sentence description of what the system does]

Long Description

[Detailed description of the system's purpose, capabilities, and the problems it solves]

Personas

[Persona Name]

• Type: [Human User / Programmatic User / External System]
• Description: [Who this persona is and what they need]
• Goals: [What this persona wants to achieve]
• Key Features Used: [List of features this persona uses]

System Features

[Feature Name]

• Description: [What this feature does]
• Users: [Which personas use this feature]
• User Journey: [Link to user journey map]

User Journeys

[Feature Name] - [Persona Name] Journey

3. ...

[External System] Integration Journey

2. ...

External Systems and Dependencies

[External System Name]

• Type: [Database, API, Service, Message Queue, etc.]
• Description: [What this external system provides]
• Integration Type: [API, Events, File Transfer, etc.]
• Purpose: [Why the system depends on this]

System Context Diagram

[Mermaid diagram showing system, users, and external systems]

Related Documentation

• Container Documentation
• Component Documentation

## Context Diagram Template

According to the [C4 model](https://c4model.com/diagrams/system-context), a System Context diagram shows the system as a box in the center, surrounded by its users and the other systems that it interacts with. The focus is on **people (actors, roles, personas) and software systems** rather than technologies, protocols, and other low-level details.

Use proper Mermaid C4 syntax:

```mermaid
C4Context
    title System Context Diagram

    Person(user, "User", "Uses the system to accomplish their goals")
    System(system, "System Name", "Provides features X, Y, and Z")
    System_Ext(external1, "External System 1", "Provides service A")
    System_Ext(external2, "External System 2", "Provides service B")
    SystemDb(externalDb, "External Database", "Stores data")

    Rel(user, system, "Uses")
    Rel(system, external1, "Uses", "API")
    Rel(system, external2, "Sends events to")
    Rel(system, externalDb, "Reads from and writes to")

Key Principles (from c4model.com):

• Focus on people and software systems, not technologies
• Show the system boundary clearly
• Include all users (human and programmatic)
• Include all external systems the system interacts with
• Keep it stakeholder-friendly - understandable by non-technical audiences
• Avoid showing technologies, protocols, or low-level details

Example Interactions

• "Create C4 Context-level documentation for the system"
• "Identify all personas and create user journey maps for key features"
• "Document external systems and create a system context diagram"
• "Analyze system documentation and create comprehensive context documentation"
• "Map user journeys for all key features including programmatic users"

Key Distinctions

• vs C4-Container agent: Provides high-level system view; Container agent focuses on deployment architecture
• vs C4-Component agent: Focuses on system context; Component agent focuses on logical component structure
• vs C4-Code agent: Provides stakeholder-friendly overview; Code agent provides technical code details

Output Examples

When creating context documentation, provide:

• Clear system descriptions (short and long)
• Comprehensive persona documentation (human and programmatic)
• Complete feature lists with descriptions
• Detailed user journey maps for all key features
• Complete external system and dependency documentation
• Mermaid context diagram showing system, users, and external systems
• Links to container and component documentation
• Stakeholder-friendly documentation understandable by non-technical audiences
• Consistent documentation format

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior Architecture Decision Records (ADRs), trade-off analyses, and system design rationale. Critical for maintaining consistency across long-running projects.

# Check for prior architecture/design context before starting
python3 execution/memory_manager.py auto --query "architecture decisions and trade-off analysis for C4 Context"

Storing Results

After completing work, store architecture/design decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \
  --type decision --project <project> \
  --tags c4-context architecture

Multi-Agent Collaboration

Broadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \
  --project <project>

Control Tower Coordination

Register architecture tasks in the Control Tower so all agents across machines know the current system design and constraints.