wshobson-agents/docs/architecture.md

Architecture & Design Principles

This marketplace follows industry best practices with a focus on granularity, composability, and minimal token usage.

Core Philosophy

Single Responsibility Principle

• Each plugin does one thing well (Unix philosophy)
• Clear, focused purposes (describable in 5-10 words)
• Average plugin size: 5.5 components (follows Anthropic's 2-8 pattern)
• Zero bloated plugins - all plugins focused and purposeful

Composability Over Bundling

• Mix and match plugins based on needs
• Workflow orchestrators compose focused plugins
• No forced feature bundling
• Clear boundaries between plugins

Context Efficiency

• Smaller tools = faster processing
• Better fit in LLM context windows
• More accurate, focused responses
• Install only what you need

Maintainability

• Single-purpose = easier updates
• Clear boundaries = isolated changes
• Less duplication = simpler maintenance
• Isolated dependencies

Granular Plugin Architecture

Plugin Distribution

• 81 focused plugins (80 local + 1 external via git-subdir) optimized for specific use cases
• 25 clear categories with 1-10 plugins each for easy discovery
• Organized by domain:
  • Development: 4 plugins (debugging, backend, frontend, multi-platform)
  • Security: 4 plugins (scanning, compliance, backend-api, frontend-mobile)
  • Operations: 4 plugins (incident, diagnostics, distributed, observability)
  • Languages: 7 plugins (Python, JS/TS, systems, JVM, scripting, functional, embedded)
  • Infrastructure: 5 plugins (deployment, validation, K8s, cloud, CI/CD)
  • And 18 more specialized categories

Component Breakdown

185 Specialized Agents

• Domain experts with deep knowledge
• Organized across architecture, languages, infrastructure, quality, data/AI, documentation, business, and SEO
• Model-optimized with three-tier strategy (Opus, Sonnet, Haiku) for performance and cost

15 Workflow Orchestrators

• Multi-agent coordination systems
• Complex operations like full-stack development, security hardening, ML pipelines, incident response
• Pre-configured agent workflows

71 Development Tools

• Optimized utilities including:
  • Project scaffolding (Python, TypeScript, Rust)
  • Security scanning (SAST, dependency audit, XSS)
  • Test generation (pytest, Jest)
  • Component scaffolding (React, React Native)
  • Infrastructure setup (Terraform, Kubernetes)

107 Agent Skills

• Modular knowledge packages
• Progressive disclosure architecture
• Domain-specific expertise across 18 plugins
• Spec-compliant (Anthropic Agent Skills Specification)

Repository Structure

claude-agents/
├── .claude-plugin/
│   └── marketplace.json          # Marketplace catalog (77 plugins)
├── plugins/                       # Isolated plugin directories
│   ├── python-development/
│   │   ├── agents/               # Python language agents
│   │   │   ├── python-pro.md
│   │   │   ├── django-pro.md
│   │   │   └── fastapi-pro.md
│   │   ├── commands/             # Python tooling
│   │   │   └── python-scaffold.md
│   │   └── skills/               # Python skills (5 total)
│   │       ├── async-python-patterns/
│   │       ├── python-testing-patterns/
│   │       ├── python-packaging/
│   │       ├── python-performance-optimization/
│   │       └── uv-package-manager/
│   ├── backend-development/
│   │   ├── agents/
│   │   │   ├── backend-architect.md
│   │   │   ├── graphql-architect.md
│   │   │   └── tdd-orchestrator.md
│   │   ├── commands/
│   │   │   └── feature-development.md
│   │   └── skills/               # Backend skills (3 total)
│   │       ├── api-design-principles/
│   │       ├── architecture-patterns/
│   │       └── microservices-patterns/
│   ├── security-scanning/
│   │   ├── agents/
│   │   │   └── security-auditor.md
│   │   ├── commands/
│   │   │   ├── security-hardening.md
│   │   │   ├── security-sast.md
│   │   │   └── security-dependencies.md
│   │   └── skills/               # Security skills (1 total)
│   │       └── sast-configuration/
│   ├── c4-architecture/
│   │   ├── agents/               # C4 architecture agents
│   │   │   ├── c4-code.md
│   │   │   ├── c4-component.md
│   │   │   ├── c4-container.md
│   │   │   └── c4-context.md
│   │   └── commands/
│   │       └── c4-architecture.md
│   └── ... (62 more isolated plugins)
├── docs/                          # Documentation
│   ├── agent-skills.md           # Agent Skills guide
│   ├── agents.md                 # Agent reference
│   ├── plugins.md                # Plugin catalog
│   ├── usage.md                  # Usage guide
│   └── architecture.md           # This file
└── README.md                      # Quick start

Plugin Structure

Each plugin contains:

• agents/ - Specialized agents for that domain (optional)
• commands/ - Tools and workflows specific to that plugin (optional)
• skills/ - Modular knowledge packages with progressive disclosure (optional)

Minimum Requirements

• At least one agent OR one command
• Clear, focused purpose
• Proper frontmatter in all files
• Entry in marketplace.json

Example Plugin

plugins/kubernetes-operations/
├── agents/
│   └── kubernetes-architect.md   # K8s architecture and design
├── commands/
│   └── k8s-deploy.md            # Deployment automation
└── skills/
    ├── k8s-manifest-generator/   # Manifest creation skill
    ├── helm-chart-scaffolding/   # Helm chart skill
    ├── gitops-workflow/          # GitOps automation skill
    └── k8s-security-policies/    # Security policy skill

Agent Skills Architecture

Progressive Disclosure

Skills use a three-tier architecture for token efficiency:

1. Metadata (Frontmatter): Name and activation criteria (always loaded)
2. Instructions: Core guidance and patterns (loaded when activated)
3. Resources: Examples and templates (loaded on demand)

Specification Compliance

All skills follow the Agent Skills Specification:

---
name: skill-name # Required: hyphen-case
description: What the skill does. Use when [trigger]. # Required: < 1024 chars
---
# Skill content with progressive disclosure

Benefits

• Token Efficiency: Load only relevant knowledge when needed
• Specialized Expertise: Deep domain knowledge without bloat
• Clear Activation: Explicit triggers prevent unwanted invocation
• Composability: Mix and match skills across workflows
• Maintainability: Isolated updates don't affect other skills

See Agent Skills for complete details on the 153 skills.

Model Configuration Strategy

Four-Tier Architecture

The system uses Claude Opus, Sonnet, Haiku, and Inherit assignments strategically:

Model	Count	Use Case
Opus	54 agents	Critical architecture, security, code review
Sonnet	62 agents	Complex tasks, support with intelligence
Haiku	20 agents	Fast operational tasks
Inherit	49 agents	Defers model choice to the user at runtime

Selection Criteria

Haiku - Fast Execution & Deterministic Tasks

• Generating code from well-defined specifications
• Creating tests following established patterns
• Writing documentation with clear templates
• Executing infrastructure operations
• Performing database query optimization
• Handling customer support responses
• Processing SEO optimization tasks
• Managing deployment pipelines

Sonnet - Complex Reasoning & Architecture

• Designing system architecture
• Making technology selection decisions
• Performing security audits
• Reviewing code for architectural patterns
• Creating complex AI/ML pipelines
• Providing language-specific expertise
• Orchestrating multi-agent workflows
• Handling business-critical legal/HR matters

Hybrid Orchestration

Combine models for optimal performance and cost:

Planning Phase (Sonnet) → Execution Phase (Haiku) → Review Phase (Sonnet)

Example:
backend-architect (Sonnet) designs API
  ↓
Generate endpoints (Haiku) implements spec
  ↓
test-automator (Haiku) creates tests
  ↓
code-reviewer (Sonnet) validates architecture

Performance & Quality

Optimized Token Usage

• Isolated plugins load only what you need
• Granular architecture reduces unnecessary context
• Progressive disclosure (skills) loads knowledge on demand
• Clear boundaries prevent context pollution

Component Coverage

• 100% agent coverage - all plugins include at least one agent
• 100% component availability - all 185 agents accessible across plugins
• Efficient distribution - 5.5 components per plugin average

Discoverability

• Clear plugin names convey purpose immediately
• Logical categorization with 23 well-defined categories
• Searchable documentation with cross-references
• Easy to find the right tool for the job

Design Patterns

Pattern 1: Single-Purpose Plugin

Each plugin focuses on one domain:

python-development/
├── agents/           # Python language experts
├── commands/         # Python project scaffolding
└── skills/           # Python-specific knowledge

Benefits:

• Clear responsibility
• Easy to maintain
• Minimal token usage
• Composable with other plugins

Pattern 2: Workflow Orchestration

Orchestrator plugins coordinate multiple agents:

full-stack-orchestration/
└── commands/
    └── full-stack-feature.md    # Coordinates 7+ agents

Orchestration:

1. backend-architect (design API)
2. database-architect (design schema)
3. frontend-developer (build UI)
4. test-automator (create tests)
5. security-auditor (security review)
6. deployment-engineer (CI/CD)
7. observability-engineer (monitoring)

Pattern 3: Agent + Skill Integration

Agents provide reasoning, skills provide knowledge:

User: "Build FastAPI project with async patterns"
  ↓
fastapi-pro agent (orchestrates)
  ↓
fastapi-templates skill (provides patterns)
  ↓
python-scaffold command (generates project)

Pattern 4: Multi-Plugin Composition

Complex workflows use multiple plugins:

Feature Development Workflow:
1. backend-development:feature-development
2. security-scanning:security-hardening
3. unit-testing:test-generate
4. comprehensive-review:full-review
5. cicd-automation:workflow-automate
6. observability-monitoring:monitor-setup

Versioning & Updates

Marketplace Updates

• Marketplace catalog in .claude-plugin/marketplace.json
• Semantic versioning for plugins
• Backward compatibility maintained
• Clear migration guides for breaking changes

Plugin Updates

• Individual plugin updates don't affect others
• Skills can be updated independently
• Agents can be added/removed without breaking workflows
• Commands maintain stable interfaces

Contributing Guidelines

Adding a Plugin

1. Create plugin directory: plugins/{plugin-name}/
2. Add agents and/or commands
3. Optionally add skills
4. Update marketplace.json
5. Document in appropriate category

Adding an Agent

1. Create plugins/{plugin-name}/agents/{agent-name}.md
2. Add frontmatter (name, description, model)
3. Write comprehensive system prompt
4. Update plugin definition

Adding a Skill

1. Create plugins/{plugin-name}/skills/{skill-name}/SKILL.md
2. Add YAML frontmatter (name, description with "Use when")
3. Write skill content with progressive disclosure
4. Add to plugin's skills array in marketplace.json

Quality Standards

• Clear naming - Hyphen-case, descriptive
• Focused scope - Single responsibility
• Complete documentation - What, when, how
• Tested functionality - Verify before committing
• Spec compliance - Follow Anthropic guidelines

See Also

• Agent Skills - Modular knowledge packages
• Agent Reference - Complete agent catalog
• Plugin Reference - All 77 plugins
• Usage Guide - Commands and workflows