MoAI-ADK is a Go-based harness that organizes and verifies Claude Code work across planning, implementation, synchronization, and review stages. Developers use it to structure agentic coding tasks, apply quality gates, and route work across language models, while the catalogue entries extend its workflow with skills, hooks, commands, MCP servers, instructions, and settings.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/modu-ai/moai-adknpx agentmods add skills/modu-ai/moai-adk/moai-platform-deploymentWrote 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/modu-ai/moai-adk/moai-platform-deployment)<a href="https://agentmods.dev/skills/modu-ai/moai-adk/moai-platform-deployment"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-platform-deployment/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/modu-ai/moai-adk/moai-platform-deployment"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-platform-deployment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 343 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00042 | $0.03101 |
| Opus 5 | $0.00021 | $0.01550 |
| Sonnet 5 | $0.00008 | $0.00620 |
| Haiku 4.5 | $0.00004 | $0.00310 |
Grade A, and why
moai-platform-deployment 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 5d 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 — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Platform Specialist
Comprehensive deployment platform guide covering Vercel (edge-first), Railway (container-first), and Convex (real-time backend).
Quick Platform Selection
When to Use Each Platform
Vercel - Edge-First Deployment:
- Next.js applications with SSR/SSG
- Global CDN distribution required
- Sub-50ms edge latency critical
- Preview deployments for team collaboration
- Managed storage needs (KV, Blob, Postgres)
Railway - Container-First Deployment:
- Full-stack containerized applications
- Custom runtime environments
- Multi-service architectures
- Persistent volume storage
- WebSocket/gRPC long-lived connections
Convex - Real-Time Backend:
- Collaborative real-time applications
- Reactive data synchronization
- TypeScript-first backend needs
- Optimistic UI updates
- Document-oriented data models
Decision Guide
By Application Type
Web Applications (Frontend + API):
- Next.js → Vercel (optimal integration)
- React/Vue with custom API → Railway (flexible)
- Real-time collaborative → Convex + Vercel
Mobile Backends:
- REST/GraphQL → Railway (stable connections)
- Real-time sync → Convex (reactive queries)
- Edge API → Vercel (global latency)
Full-Stack Monoliths:
- Containerized → Railway (Docker support)
- Serverless → Vercel (Next.js API routes)
- Real-time → Convex (built-in reactivity)
By Infrastructure Needs
Compute Requirements:
- Edge compute → Vercel (30+ edge locations)
- Custom runtimes → Railway (Docker flexibility)
- Serverless TypeScript → Convex (managed runtime)
Storage Requirements:
- Redis/KV → Vercel KV or Railway
- PostgreSQL → Vercel Postgres or Railway
- File storage → Vercel Blob or Railway volumes
- Document DB → Convex (built-in)
Networking Requirements:
- CDN distribution → Vercel (built-in)
- Private networking → Railway (service mesh)
- Real-time WebSocket → Convex (built-in) or Railway
Common Deployment Patterns
Pattern 1: Next.js with Database
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.
- 5d ago First seen · 456 lines · 42 tokens per session scan A a723eca9a921
moai-platform-deployment is a skill published in the GitHub repository modu-ai/moai-adk (1,204 stars, last pushed today), licensed Apache-2.0. It adds 42 tokens to every session and 3,101 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.
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