| name | nw-command-design-patterns |
| description | Best practices for command definition files - size targets, declarative template, anti-patterns, and canonical examples based on research evidence |
| user-invocable | false |
| disable-model-invocation | true |
Command Design Patterns (composing core)
Kind: KNOWLEDGE (lean composing core). The command-design knowledge is decomposed into three one-trigger modules; this core holds the canonical examples and composes the modules by trigger. Load the module(s) for the question in play.
Composition
| Module | Load when the question is | Path |
|---|
nw-command-design-patterns-classification | what CATEGORY / what SIZE / what SHAPE (declarative template, WHAT-vs-HOW logic placement) | ~/.claude/skills/nw-command-design-patterns-classification/SKILL.md |
nw-command-design-patterns-reduction | what is REDUCIBLE / what to REMOVE / how far to COMPRESS (duplication triangle, anti-patterns, compression rules) | ~/.claude/skills/nw-command-design-patterns-reduction/SKILL.md |
nw-command-design-patterns-authoring | I am creating a NEW command — which FILES / what FORMAT (v2.8+ three-file install contract) | ~/.claude/skills/nw-command-design-patterns-authoring/SKILL.md |
The three triggers partition the space: classification (size an existing command), reduction (trim a bloated one), authoring (lay out a new one). No overlap, no gap.
Canonical Examples
Example 1: Minimal Dispatcher (forge.md pattern, ~40 lines)
# DW-FORGE: Create Agent (V2)
**Wave**: CROSS_WAVE
**Agent**: Zeus (nw-agent-builder)
## Overview
Create a new agent using the research-validated v2 approach.
## Agent Invocation
@nw-agent-builder
Execute \*forge to create {agent-name} agent.
**Configuration:**
- agent_type: specialist | reviewer | orchestrator
## Success Criteria
- [ ] Agent definition under 400 lines
- [ ] 11-point validation checklist passes
- [ ] 3-5 canonical examples included
## Next Wave
**Handoff To**: Agent installation and deployment
**Deliverables**: Agent specification file + Skill files
Example 2: Medium Dispatcher with Context (~80 lines)
# DW-RESEARCH: Evidence-Driven Research
**Wave**: CROSS_WAVE
**Agent**: Nova (nw-researcher)
## Overview
Execute systematic evidence-based research with source verification.
## Orchestration: Trusted Source Config
Read .nwave/trusted-source-domains.yaml at orchestration time, embed inline in prompt.
## Agent Invocation
@nw-researcher
Execute \*research on {topic} [--embed-for={agent-name}].
**Configuration:**
- research_depth: detailed
- output_directory: docs/research/
## Success Criteria
- [ ] All sources from trusted domains
- [ ] Cross-reference performed (3+ sources per major claim)
- [ ] Research file created in docs/research/
## Next Wave
**Handoff To**: Invoking workflow
**Deliverables**: Research document + optional embed file
Example 3: Orchestrator (~200 lines)
Coordinates multiple phases without embedding agent knowledge:
# DW-DOCUMENT: Documentation Creation
**Wave**: CROSS_WAVE
**Agent**: Orchestrator (self)
## Overview
Create DIVIO-compliant documentation through research and writing phases.
## Phases
1. Research phase: @nw-researcher gathers domain knowledge
2. Writing phase: @nw-documentarist creates documentation
3. Review phase: @nw-reviewer validates quality
## Phase 1: Research
@nw-researcher - Execute \*research on {topic}
[Orchestrator reads and passes relevant context files]
## Phase 2: Writing
@nw-documentarist - Create {doc-type} documentation
[Orchestrator passes research output as context]
## Phase 3: Review
@nw-reviewer - Review documentation against DIVIO standards
[Orchestrator passes documentation for review]
## Success Criteria
[Per-phase and overall criteria]
The orchestrator describes WHAT each phase does and WHO does it. The agents know HOW.
