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.
git 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/commands/nwave-ai/nwave/devops)<a href="https://agentmods.dev/commands/nwave-ai/nwave/devops"><img src="https://agentmods.dev/badge/commands/nwave-ai/nwave/devops.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 5.1 | $0.00024 | $0.02705 |
| Opus 5 | $0.00012 | $0.01352 |
| Sonnet 5 | $0.00005 | $0.00541 |
| Haiku 4.5 | $0.00002 | $0.00270 |
Grade A, and why
devops 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 yesterday.
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 — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NW-DEVOPS: Platform Readiness and Infrastructure Design
Wave: DEVOPS (wave 4 of 6) | Agent: Apex (nw-platform-architect) | Command: /nw-devops
Overview
Execute DEVOPS wave: platform readiness|CI/CD pipeline setup|observability design|infrastructure preparation. Positioned between DESIGN and DISTILL (DISCOVER > DISCUSS > SPIKE > DESIGN > DEVOPS > DISTILL > DELIVER), ensures infrastructure is ready before acceptance tests and code.
Apex translates DESIGN architecture decisions into operational infrastructure: CI/CD pipelines|logging|monitoring|alerting|observability.
Interactive Decision Points
Before proceeding, the orchestrator asks:
Decision 1: Deployment Target
Question: What is the deployment target? Options:
- Cloud-native -- AWS, GCP, Azure managed services
- On-premise -- self-hosted infrastructure
- Hybrid -- mix of cloud and on-premise
- Edge -- distributed edge deployment
- Other -- user provides custom input
Decision 2: Container Orchestration
Question: Container orchestration approach? Options:
- Kubernetes -- full orchestration
- Docker Compose -- lightweight container management
- Serverless -- function-as-a-service, no containers
- None -- bare metal or VM-based deployment
Decision 3: CI/CD Platform
Question: CI/CD platform preference? Options:
- GitHub Actions
- GitLab CI
- Jenkins
- Azure DevOps
- Other -- user provides custom input
Decision 4: Existing Infrastructure
Question: Is there existing infrastructure or CI/CD to integrate with? Options:
- Yes, both -- describe existing infrastructure and CI/CD (user provides details)
- Existing infra only -- infrastructure exists, CI/CD is greenfield
- Existing CI/CD only -- CI/CD exists, infrastructure is greenfield
- No -- greenfield, design everything from scratch
Decision 5: Observability and Logging
Question: What observability and logging approach? Options:
- Prometheus + Grafana (metrics) with structured JSON logs
- Datadog (full-stack observability including logs)
- ELK stack (Elasticsearch, Logstash, Kibana for logs and metrics)
- OpenTelemetry (vendor-agnostic telemetry) with provider of choice
- CloudWatch (AWS-native metrics and logging)
- Custom -- user provides details
- None -- defer observability setup
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.
- yesterday First seen · 251 lines · 24 tokens per session scan A 16fed511ead3
devops is a command published in the GitHub repository nWave-ai/nWave (608 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 2,705 once invoked, about $0.0001 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 2026-09-06.
Other commands, from other repositories
ops-vercel
Command "ops-vercel" from christopherlouet/claude-base, covering ops-vercel agent (pointer), context, delegate to the vendor toolkit and related agents.
ops-infra-code
Implements Infrastructure as Code (IaC) with Terraform, CloudFormation or Pulumi.
ops-serverless
Deployment of serverless applications (AWS Lambda, Vercel, Cloudflare Workers).
fix-develop
Autonomous fix loop for failing CI on the repo's default branch.
cf-scaffold-project
Scaffold a Cloudflare project — Worker, Pages, or Worker+D1+R2 starter — with Wrangler config, Terraform skeleton, and GitHub Actions deploy using scoped API tokens.
workflow-create
Command "workflow-create" from smith-horn/skillsmith, covering workflow-create, usage, options, examples and author deploy-api.yaml, then register it as a template.