# C4 Context > Expert C4 Context-level documentation specialist. Creates high-level system context diagrams, documents personas, user journeys, system features, and external dependencies. Use when this capability is needed. - Skill: `tomevault-io/c4-context` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/c4-context` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/c4-context/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/c4-context --- # C4 Context Level: System Context ## Use this skill when - Working on c4 context level: system context tasks or workflows - Needing guidance, best practices, or checklists for c4 context level: system context ## Do not use this skill when - The task is unrelated to c4 context level: system context - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## System Overview ### Short Description [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 1. [Step 1]: [Description] 2. [Step 2]: [Description] 3. [Step 3]: [Description] ... ### [External System] Integration Journey 1. [Step 1]: [Description] 2. [Step 2]: [Description] ... ## 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](https://c4model.com/diagrams/system-context)): - 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](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/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. ```bash # 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: ```bash python3 execution/memory_manager.py store \ --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \ --type decision --project \ --tags c4-context architecture ``` ### Multi-Agent Collaboration Broadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns. ```bash python3 execution/cross_agent_context.py store \ --agent "" \ --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \ --project ``` ### Control Tower Coordination Register architecture tasks in the Control Tower so all agents across machines know the current system design and constraints. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.