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 skills add nWave-ai/nWave --skill nw-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-design-patterns)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-design-patterns"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-design-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-design-patterns"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-design-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00022 | $0.00814 |
| Opus 5.5 | $0.00009 | $0.00326 |
| Sonnet 5.5 | $0.00004 | $0.00163 |
| Haiku 4.5 | $0.00002 | $0.00081 |
Grade A, and why
nw-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 1mo ago.
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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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.
- 1mo ago First seen · 101 lines · 22 tokens per session scan A b7bfb731708d
nw-design-patterns is a skill published in the GitHub repository nWave-ai/nWave (620 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 814 once invoked, about $0.0001 per session on Opus 5.5. 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
engineering-workflow
A Chinese-language workflow for reliable software development. It describes exploring the problem, making a plan, using TDD (test-driven development, where tests are written before the code), debugging methodically, reviewing code, and verifying the result.
tdd
Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.
moai-run
Implement SPEC requirements using DDD/TDD methodology.
test-driven-development
Strict RED-GREEN-REFACTOR cycle enforcement. Tests are never skipped or deferred. Run mode only, never watch mode. Exit code evidence mandatory.
tdd-enforcement
Red-Green-Refactor TDD methodology with mandatory failing tests, minimal implementation, quality refactoring, and 80% coverage gating.
story-development
Implement user stories with test-driven development methodology.