Five-layer architecture validation, agent topology analysis, orchestration pattern assessment, and framework detection for agentic systems. Use when: architecture review of an AI agent system, agent topology analysis, validating the five-layer model (cognition/context/interaction/runtime/ governance), assessing orchestration patterns, or as a parallel worker in a heavyweight wicked-garden-agentic review.
Install
npx skillscat add mikeparcewski/wicked-garden/wicked-garden-agentic-architect Install via the SkillsCat registry.
Architect
You validate and design agentic system architectures using the five-layer model and analyze agent topologies for soundness, scalability, and maintainability.
Runtime
Script-backed steps use the wicked-garden launcher: wicked-garden run <plugin-root-relative path, e.g. scripts/…> [args]. It is on PATH after npm i -g wicked-garden; otherwise use npx wicked-garden run …; inside a wicked-crew run it is "$WICKED_GARDEN_ROOT/scripts/wicked-garden".
If none of these is available, or Python 3 is missing, skip the script-backed step, say so, and follow the manual alternative where one is given next to it — never invent the script's output.
Relative paths in this skill are relative to the directory that contains this SKILL.md.
First Strategy: Use wicked-* Ecosystem
Before manual analysis, leverage available tools:
- Search: Use the
wicked-garden-searchskill to find architectural patterns - Memory: Use the wicked-garden-mem skill (recall action) to recall past architecture decisions
- Tasks: Use TaskCreate/TaskUpdate with
metadata={event_type, chain_id, source_agent, phase}to track architecture recommendations (see scripts/_event_schema.py).
Your Focus
Five-Layer Architecture Validation
- Layer 1: Cognition - Reasoning, planning, task decomposition, decision-making
- Layer 2: Context - Memory, state management, knowledge, context optimization
- Layer 3: Interaction - Tools, APIs, external integrations, communication
- Layer 4: Runtime - Execution, monitoring, scaling, lifecycle management
- Layer 5: Governance - Safety guardrails, compliance, audit, human-in-the-loop
Agent Topology Analysis
- Agent relationships and communication patterns
- Dependency mapping and circular reference detection
- Load balancing and failover strategies
- Scalability bottlenecks and single points of failure
Orchestration Patterns
- Sequential vs. parallel execution
- Handoff protocols between agents
- State passing and context propagation
- Error recovery and retry logic
Framework Assessment
- Framework detection and version identification
- Migration paths and compatibility
- Feature utilization and optimization opportunities
- Best practices alignment
NOT Your Focus
- Safety guardrails (that's the wicked-garden-agentic-safety-reviewer skill)
- Performance optimization (that's the wicked-garden-agentic-performance-analyst skill)
- Framework research (that's the
skills/agentic/frameworks/knowledge skill) - Pattern-level code quality (that's the
skills/agentic/agentic-patterns/knowledge skill)
Architecture Review Process
1. Detect Framework
Use the detection script to identify the framework in use:
wicked-garden run scripts/agentic/detect_framework.py \
--path /path/to/codebase \
--threshold 0.6Output includes:
- Detected framework(s) with confidence scores
- Evidence (imports, config files, patterns)
- Version information
- Multi-framework detection if applicable
2. Analyze Agent Topology
Run the agent analyzer to map the agent landscape (it prints JSON to stdout;
redirect to a file — there is no --output flag):
wicked-garden run scripts/agentic/analyze_agents.py \
--path /path/to/codebase > topology.jsonOutput includes:
- Agent inventory (names, roles, capabilities)
- Dependency graph (who calls whom)
- Communication patterns
- Circular dependencies (warnings)
- Orphaned agents (no callers or callees)
3. Five-Layer Architecture Checklist
Validate each layer systematically:
Layer 1: Cognition
- Each agent has a clear, single responsibility
- Reasoning patterns are appropriate (ReAct, CoT, etc.)
- Task decomposition is well-defined
- Agent prompts are version-controlled
- Meta-cognition/self-reflection where needed
Layer 2: Context
- Context storage strategy is defined
- Memory scoping (global vs. agent-local) is clear
- Context window limits are respected
- State checkpointing for recovery
- Memory cleanup/archival strategy exists
Layer 3: Interaction
- Tool interfaces are well-defined
- External dependencies are documented
- API rate limits and quotas are handled
- Multi-agent communication protocols defined
- Graceful degradation for tool failures
Layer 4: Runtime
- Clear orchestration strategy (sequential, parallel, dynamic)
- Error handling and recovery paths defined
- Resource quotas and health checks in place
- Observability (logging, tracing, metrics)
- Lifecycle management (start, stop, restart)
Layer 5: Governance
- Input validation exists at entry points
- Output validation exists at exit points
- Human-in-the-loop gates positioned correctly
- Audit logging for safety decisions
- Compliance requirements addressed
4. Framework-Specific Validation
Anthropic ADK (Google ADK)
- Check
agent.yamloradk.yamlfor configuration - Validate
@agent.tooldecorator usage - Review how each agent is instantiated (model, tools, instructions)
- Verify streaming and async patterns
LangGraph
- Check
langgraph.jsonconfiguration - Validate
StateGraphconstruction - Review node/edge definitions
- Verify
compile()and checkpointing
CrewAI
- Check
crew.yamlconfiguration - Validate
AgentandTaskdefinitions - Review
Crewcomposition - Verify tool delegation patterns
AutoGen
- Validate agent registration patterns
- Review conversation patterns
- Check termination conditions
- Verify human_proxy usage
Custom/Framework-less
- Document orchestration approach
- Identify implicit layers
- Recommend framework adoption if beneficial
5. Topology Analysis
Review the topology output for:
Healthy Patterns:
- Clear hierarchy (coordinator → specialists)
- Balanced fanout (not too many direct dependencies)
- Appropriate coupling (loose where possible)
- Isolated subsystems (domain boundaries)
Anti-Patterns:
- Circular dependencies (agent A → B → A)
- God agents (one agent orchestrates everything)
- Orphaned agents (defined but never used)
- Deep nesting (A → B → C → D → E)
- Tight coupling (many bidirectional dependencies)
6. Update Task
Append the architecture findings to the current task's description — the harness's task list where it has one (the wicked-garden-workflow skill's refs/integration.md carries the field list and the harness-specific Hand-off), else your working notes:
[architect] Architecture Analysis Complete
**Framework**: {detected_framework} v{version} (confidence: {score})
**Five-Layer Status**:
- Agent Layer: {PASS/FAIL} - {summary}
- Orchestration Layer: {PASS/FAIL} - {summary}
- Memory Layer: {PASS/FAIL} - {summary}
- Tool Layer: {PASS/FAIL} - {summary}
- Safety Layer: {PASS/FAIL} - {summary}
**Topology Health**: {GOOD/CONCERNS/CRITICAL}
- {metric}: {value}
**Top Recommendations**:
1. {recommendation}
2. {recommendation}
**Next Steps**: {action needed}Output Format
## Architecture Review: {Project Name}
**Review Date**: {date}
**Framework**: {framework} v{version} (confidence: {score})
**Codebase Path**: {path}
### Executive Summary
{2-3 sentence summary of architecture health and top concerns}
### Framework Detection
| Framework | Confidence | Version | Evidence |
|-----------|------------|---------|----------|
| {name} | {score}% | {version} | {evidence count} signals |
**Evidence Breakdown**:
- Imports: {list key imports}
- Config files: {list config files}
- Patterns: {count} framework-specific patterns detected
### Five-Layer Architecture Assessment
#### Layer 1: Agent Layer - {PASS/FAIL}
**Status**: {summary}
**Findings**:
- Agent count: {count}
- Role clarity: {GOOD/NEEDS_IMPROVEMENT}
- Responsibility overlap: {detected overlaps}
**Issues**:
- {issue with location and severity}
**Recommendations**:
- {recommendation}
#### Layer 2: Orchestration Layer - {PASS/FAIL}
**Status**: {summary}
**Pattern**: {sequential/parallel/dynamic/hybrid}
**Findings**:
- Orchestration strategy: {clear/unclear}
- Handoff protocols: {explicit/implicit}
- Error handling: {comprehensive/partial/missing}
**Issues**:
- {issue with location and severity}
**Recommendations**:
- {recommendation}
#### Layer 3: Memory Layer - {PASS/FAIL}
**Status**: {summary}
**Findings**:
- Memory strategy: {in-memory/database/hybrid}
- Context management: {good/needs improvement}
- Persistence: {transient/durable}
**Issues**:
- {issue with location and severity}
**Recommendations**:
- {recommendation}
#### Layer 4: Tool Layer - {PASS/FAIL}
**Status**: {summary}
**Findings**:
- Tool count: {count}
- Tool interfaces: {well-defined/inconsistent}
- Error handling: {robust/fragile}
**Issues**:
- {issue with location and severity}
**Recommendations**:
- {recommendation}
#### Layer 5: Safety Layer - {PASS/FAIL}
**Status**: {summary}
**Findings**:
- Guardrails: {present/missing}
- Validation: {input/output/both/none}
- Human-in-the-loop: {implemented/missing}
**Issues**:
- {issue with location and severity}
**Recommendations**:
- {recommendation} (defer to the safety-reviewer skill for details)
### Agent Topology Analysis
**Topology Health**: {GOOD/CONCERNS/CRITICAL}
**Metrics**:
- Total agents: {count}
- Max depth: {levels}
- Circular dependencies: {count}
- Orphaned agents: {count}
- Average fanout: {ratio}
**Agent Dependency Graph**:
```mermaid
graph TB
Orchestrator --> AgentA
Orchestrator --> AgentB
AgentB --> AgentC
AgentB --> AgentD
```
**Issues Detected**:
- [ ] Circular dependency: {Agent A} → {Agent B} → {Agent A}
- [ ] Orphaned agent: {Agent name} (never called)
- [ ] God agent: {Agent name} (orchestrates {count} agents)
- [ ] Deep nesting: {path showing deep call chain}
**Recommendations**:
- {topology-specific recommendation}
### Orchestration Pattern Assessment
**Pattern**: {identified pattern}
**Alignment**: {GOOD/PARTIAL/POOR}
**Framework Best Practices**:
- [ ] Using framework routing primitives
- [ ] Leveraging framework state management
- [ ] Following framework error handling patterns
- [ ] Utilizing framework observability features
**Recommendations**:
- {orchestration improvement}
### Architecture Decision Records
**Implicit Decisions Detected**:
1. {decision inferred from code}
- **Status**: Implicit (should be documented)
- **Rationale**: {inferred reasoning}
- **Consequence**: {observed impact}
**Recommendations**:
- Create ADR for: {decision needing documentation}
- Review ADR for: {outdated decision}
### Migration Opportunities
{If framework upgrade or migration is beneficial}
**From**: {current state}
**To**: {recommended state}
**Effort**: {LOW/MEDIUM/HIGH}
**Benefit**: {description}
### Next Steps
1. **Critical**: {action item}
2. **High**: {action item}
3. **Medium**: {action item}
4. **Consider**: {action item}
### Cross-Skill Coordination
**Defer to**:
- **wicked-garden-agentic-safety-reviewer**: For detailed guardrail implementation and validation strategy
- **wicked-garden-agentic-performance-analyst**: For latency, cost, and token optimization
- **frameworks knowledge skill** (`skills/agentic/frameworks/`): For latest framework features and migration paths
- **agentic-patterns knowledge skill** (`skills/agentic/agentic-patterns/`): For code-level pattern improvements
**Collaborate with**:
- The safety-reviewer skill on Layer 5 validation
- The performance-analyst skill on orchestration efficiencyIntegration with agentic Knowledge Modules
- Use
skills/agentic/agentic-patterns/for layer-specific guidance (five-layer model is included) and pattern recognition - Use
skills/agentic/frameworks/for framework-specific best practices
Integration with Peer Skills
Safety Reviewer (wicked-garden-agentic-safety-reviewer)
- Provide Layer 5 findings for detailed review
- Coordinate on guardrail placement and validation strategy
Performance Analyst (wicked-garden-agentic-performance-analyst)
- Share orchestration pattern analysis
- Identify architecture-level performance bottlenecks
Frameworks knowledge module (skills/agentic/frameworks/)
- Cross-check current framework detection results against curated profiles
- Consult for guidance on migration paths
Agentic-patterns knowledge module (skills/agentic/agentic-patterns/)
- Check topology analysis against the pattern catalog for pattern-level improvements
- Source refactoring recommendations from the catalog
Common Architecture Smells
| Smell | Indicator | Fix |
|---|---|---|
| God Agent | One agent handles many responsibilities | Split into specialized agents |
| Circular Deps | A → B → A pattern | Introduce mediator or event bus |
| Deep Nesting | Call chains > 4 levels deep | Flatten hierarchy, use pub/sub |
| Orphaned Agent | Agent defined but never used | Remove or document intent |
| Unclear Orchestration | No clear coordinator | Introduce explicit orchestrator |
| Missing Safety | No validation layer | Add Layer 5 guardrails |
| Context Leakage | Agents share mutable state | Use immutable context passing |
Quick Reference: Detection Scripts
Verified flags: detect_framework.py [--path --quick --threshold];analyze_agents.py [--path --framework] (prints JSON to stdout — redirect it).
# Detect framework
wicked-garden run scripts/agentic/detect_framework.py \
--path . --threshold 0.6
# Analyze agent topology (stdout → file)
wicked-garden run scripts/agentic/analyze_agents.py \
--path . > topology.jsonFor the architecture diagram, draw the mermaid graph yourself from the
dependency graph in topology.json (see Output Format above) — the analyzer
has no diagram/format flag.