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/data-wise/craft/devops-helpernpx skills add Data-Wise/craft --skill devops-helpergit clone --depth 1 https://github.com/Data-Wise/craftWhat 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 | $0.00052 | $0.01342 |
| Opus 5 | $0.00026 | $0.00671 |
| Sonnet 5 | $0.00010 | $0.00268 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
devops-helper 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 2d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DevOps Helper Skill
Auto-activated when: User discusses deployment, CI/CD, Docker, testing automation, or infrastructure decisions.
Core Capabilities
1. CI/CD Pipelines
- GitHub Actions workflow design
- Test automation (unit, integration, e2e)
- Build optimization
- Deployment strategies (blue/green, canary, rolling)
- Secrets management
2. Containerization
- Dockerfile best practices (multi-stage builds)
- Docker Compose for local dev
- Image optimization (layer caching, size reduction)
- Container orchestration (when needed)
3. Deployment Platforms
- Platform selection (Vercel, Render, Fly.io, Railway)
- Cost optimization strategies
- Database hosting (Supabase, PlanetScale, Neon)
- Static site hosting (Netlify, GitHub Pages)
4. Testing Automation
- Test pyramid (unit > integration > e2e)
- Pre-commit hooks (Husky, lint-staged)
- Code quality gates (coverage thresholds)
- Performance testing basics
Design Philosophy: Solid Indie
Ship Fast Principles:
- Start with platform-as-a-service (Vercel, Render)
- Use managed databases (don't self-host Postgres initially)
- Automate tests, but don't obsess over 100% coverage
- Monitor errors (Sentry), not metrics initially
Right-Sized DevOps:
- Solo/small team: GitHub Actions + Vercel
- Need scaling: Add Fly.io or Railway
- Need full control: Then consider AWS/GCP (not before)
Anti-Patterns to Avoid:
- ❌ Kubernetes for < 10 person teams
- ❌ Self-hosted infrastructure before product-market fit
- ❌ Complex multi-environment setups (dev/staging/prod initially)
- ❌ Over-monitoring (start with errors, add metrics later)
Delegation Strategy
When analysis is needed, I will:
- Quick assessment - Identify DevOps problem
- Delegate to agents when feasible:
devops-engineeragent for pipeline optimizationexperienced-engineeragent for testing strategyperformance-engineeragent for build performance
- Run in background - Use Task tool with
run_in_background: true - Synthesize results - Provide actionable DevOps recommendations
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.
- 2d ago First seen · 190 lines · 52 tokens per session scan A 57293546ffab
devops-helper is a skill published in the GitHub repository Data-Wise/craft (4 stars, last pushed 16d ago), licensed MIT. It adds 52 tokens to every session and 1,342 once invoked, about $0.0003 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 2026-08-31.
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