Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nwave-ai/nwave/nw-command-design-patternsnpx skills add nWave-ai/nWave --skill nw-command-design-patternsgit clone --depth 1 https://github.com/nWave-ai/nWaveWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nwave-ai/nwave/nw-command-design-patterns)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-command-design-patterns"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-command-design-patterns.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00031 | $0.02260 |
| Opus 5 | $0.00015 | $0.01130 |
| Sonnet 5 | $0.00006 | $0.00452 |
| Haiku 4.5 | $0.00003 | $0.00226 |
Grade A, and why
nw-command-design-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command Design Patterns
The Forge Model (Gold Standard)
forge.md at 40 lines is the reference dispatcher. Contains: header (wave, agent, overview) | Agent invocation (name + command + config) | Success criteria (checklist) | Next wave handoff | Expected outputs. Every dispatcher should aspire to this pattern.
Command Categories
| Category | Description | Size Target | Examples |
|---|---|---|---|
| Simple | Direct action, minimal delegation | 40-80 lines | forge, start, version, git |
| Dispatcher | Delegates to one agent with context | 40-150 lines | research, review, execute |
| Orchestrator | Coordinates multiple agents/phases | 100-300 lines | develop, document |
Declarative Command Template
Commands declare WHAT, not HOW. The agent knows how to do its job.
# DW-{NAME}: {Title}
**Wave**: {WAVE_NAME}
**Agent**: {persona} ({agent-id})
## Overview
One paragraph: what this command does and when to use it.
## Context Files Required
- {path} - {why needed}
## Agent Invocation
@{agent-id}
Execute \*{command} for {parameters}.
**Context Files:**
- {files the orchestrator reads and passes}
**Configuration:**
- {key}: {value} # {comment}
## Success Criteria
- [ ] {measurable outcome}
- [ ] {quality gate}
## Next Wave
**Handoff To**: {next wave or workflow step}
**Deliverables**: {what this command produces}
# Expected outputs:
# - {file paths}
Size Targets and Evidence
Research (Chroma Research, Anthropic context engineering): focused prompts (~300 tokens) outperform full prompts (~113k tokens) | Claude shows most pronounced performance gap | Information buried mid-prompt gets deprioritized ("Lost in the Middle") | Opus 4.6 is proactive/self-directing; verbose instructions cause overtriggering
Targets: Dispatchers 40-150 lines | Orchestrators 100-300 lines | Current average 437 lines; target under 150
The Duplication Triangle
Commands duplicate content in three directions, all waste tokens:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 282 lines · 31 tokens per session scan A a406791ea417
nw-command-design-patterns is a skill published in the GitHub repository nWave-ai/nWave (604 stars, last pushed 4d ago), licensed MIT. It adds 31 tokens to every session and 2,260 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
smoke-test
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke…
vercel-deploy
Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
agent-repo-architect
Agent skill for repo-architect - invoke with $agent-repo-architect.
skill-reviewer
Reviews DeerFlow skill packages for readiness, triggers, safety boundaries, resources, and evidence. Invoke when users ask to audit, grade, or production-check an existing skill.
agent-github-modes
Agent skill for github-modes - invoke with $agent-github-modes.
agent-code-analyzer
Agent skill for code-analyzer - invoke with $agent-code-analyzer.