/nw-design-patterns
7 agentic design patterns with decision tree for choosing the right pattern for each agent type
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7 agentic design patterns with decision tree for choosing the right pattern for each agent type
SKILL.md
nw-design-patterns.SKILL.mdname: nw-design-patterns
description: 7 agentic design patterns with decision tree for choosing the right pattern for each agent type
user-invocable: false
disable-model-invocation: true
Agentic Design Patterns
Pattern Decision Tree
Is the agent doing a single focused task?
YES -> Does it need self-evaluation?
YES -> Reflection
NO -> ReAct (default for most agents)
NO -> Is it coordinating multiple agents?
YES -> Are tasks independent?
YES -> Parallel Orchestration
NO -> Are tasks sequential with dependencies?
YES -> Sequential Orchestration
NO -> Hierarchical (supervisor + workers)
NO -> Is it routing to one of several specialists?
YES -> Router
NO -> Does it need structured task decomposition?
YES -> Planning
NO -> ReAct (default)1. ReAct (Reason + Act)
General-purpose agents needing tool calling and iterative problem-solving.
**Loop**: Reason -> Select/execute action -> Observe result -> Repeat until done. **When**: Default pattern. Most specialist agents. **Examples**: software-crafter, researcher, troubleshooter.
2. Reflection
Agent must evaluate and iteratively improve its own output.
**Loop**: Generate -> Review against criteria -> Identify gaps -> Refine -> Validate threshold met. **When**: Quality-critical outputs where first-draft insufficient (code review, architecture review, agent validation). **Examples**: agent-builder-reviewer, solution-architect-reviewer, software-crafter-reviewer.
3. Router
Request classified and delegated to exactly one specialist.
**Loop**: Analyze request -> Classify -> Select specialist -> Delegate. **When**: Task dispatching, single path execution. Low overhead, fast routing. **Examples**: workflow-dispatcher, task-router.
4. Planning
Complex tasks requiring structured decomposition before execution.
**Loop**: Decompose into sub-tasks -> Sequence -> Allocate resources -> Execute with checkpoints. **When**: Multi-step implementations, migrations, large refactoring. **Examples**: project-planner, migration-coordinator.
5. Sequential Orchestration
Linear workflows with clear dependencies between stages.
**Structure**: Agent1 -> Output1 -> Agent2 -> Output2 -> Agent3 -> Result **When**: Pipeline workflows where each stage transforms previous output. **Example**: nWave waves: DISCUSS -> DESIGN -> DEVOPS -> DISTILL -> DELIVER.
6. Parallel Orchestration
Multiple independent analyses needed simultaneously.
**Structure**: Supervisor -> [Worker1, Worker2, Worker3] (concurrent) -> Aggregate results. **When**: Independent analyses, multi-aspect reviews, parallel risk assessment. **Example**: Multi-reviewer code review, parallel security + performance + correctness analysis.
7. Hierarchical
Supervisor coordinates multiple worker agents dynamically.
**Structure**: Supervisor manages workers, routing tasks and aggregating results. **When**: Complex coordination where routing depends on intermediate results. **Example**: feature-coordinator supervising frontend/backend/database/testing specialists.
Pattern Combinations
- **ReAct + Reflection**: Reason/act then self-review (most reviewer agents)
- **Planning + Sequential**: Decompose then execute pipeline (devop)
- **Router + Hierarchical**: Route to supervisor who coordinates workers
Choosing for nWave Agents
| Agent Role | Pattern | Rationale | |-----------|---------|-----------| | Specialist (single domain) | ReAct | Tool-using, iterative task completion | | Reviewer (-reviewer suffix) | Reflection | Must self-evaluate and iterate on critique | | Wave orchestrator | Sequential | Clear dependency chain between phases | | Multi-agent coordinator | Hierarchical | Dynamic task routing to specialists | | Task dispatcher | Router | Classification and single-path delegation |
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name: nw-design-patterns description: 7 agentic design patterns with decision tree for choosing the right pattern for each agent type user-invocable: false disable-model-invocation: true
Agentic Design Patterns
Pattern Decision Tree
Is the agent doing a single focused task?
YES -> Does it need self-evaluation?
YES -> Reflection
NO -> ReAct (default for most agents)
NO -> Is it coordinating multiple agents?
YES -> Are tasks independent?
YES -> Parallel Orchestration
NO -> Are tasks sequential with dependencies?
YES -> Sequential Orchestration
NO -> Hierarchical (supervisor + workers)
NO -> Is it routing to one of several specialists?
YES -> Router
NO -> Does it need structured task decomposition?
YES -> Planning
NO -> ReAct (default)1. ReAct (Reason + Act)
General-purpose agents needing tool calling and iterative problem-solving.
**Loop**: Reason -> Select/execute action -> Observe result -> Repeat until done. **When**: Default pattern. Most specialist agents. **Examples**: software-crafter, researcher, troubleshooter.
2. Reflection
Agent must evaluate and iteratively improve its own output.
**Loop**: Generate -> Review against criteria -> Identify gaps -> Refine -> Validate threshold met. **When**: Quality-critical outputs where first-draft insufficient (code review, architecture review, agent validation). **Examples**: agent-builder-reviewer, solution-architect-reviewer, software-crafter-reviewer.
3. Router
Request classified and delegated to exactly one specialist.
**Loop**: Analyze request -> Classify -> Select specialist -> Delegate. **When**: Task dispatching, single path execution. Low overhead, fast routing. **Examples**: workflow-dispatcher, task-router.
4. Planning
Complex tasks requiring structured decomposition before execution.
**Loop**: Decompose into sub-tasks -> Sequence -> Allocate resources -> Execute with checkpoints. **When**: Multi-step implementations, migrations, large refactoring. **Examples**: project-planner, migration-coordinator.
5. Sequential Orchestration
Linear workflows with clear dependencies between stages.
**Structure**: Agent1 -> Output1 -> Agent2 -> Output2 -> Agent3 -> Result **When**: Pipeline workflows where each stage transforms previous output. **Example**: nWave waves: DISCUSS -> DESIGN -> DEVOPS -> DISTILL -> DELIVER.
6. Parallel Orchestration
Multiple independent analyses needed simultaneously.
**Structure**: Supervisor -> [Worker1, Worker2, Worker3] (concurrent) -> Aggregate results. **When**: Independent analyses, multi-aspect reviews, parallel risk assessment. **Example**: Multi-reviewer code review, parallel security + performance + correctness analysis.
7. Hierarchical
Supervisor coordinates multiple worker agents dynamically.
**Structure**: Supervisor manages workers, routing tasks and aggregating results. **When**: Complex coordination where routing depends on intermediate results. **Example**: feature-coordinator supervising frontend/backend/database/testing specialists.
Pattern Combinations
- **ReAct + Reflection**: Reason/act then self-review (most reviewer agents)
- **Planning + Sequential**: Decompose then execute pipeline (devop)
- **Router + Hierarchical**: Route to supervisor who coordinates workers
Choosing for nWave Agents
| Agent Role | Pattern | Rationale | |-----------|---------|-----------| | Specialist (single domain) | ReAct | Tool-using, iterative task completion | | Reviewer (-reviewer suffix) | Reflection | Must self-evaluate and iterate on critique | | Wave orchestrator | Sequential | Clear dependency chain between phases | | Multi-agent coordinator | Hierarchical | Dynamic task routing to specialists | | Task dispatcher | Router | Classification and single-path delegation |
AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
Repo: nWave-ai/nWave
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