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/MN-Lizard-Team/aiyu-multi-agentWrote 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/rules/mn-lizard-team/aiyu-multi-agent/containerization)<a href="https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/containerization"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/containerization.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 | $0.00015 | $0.01057 |
| Opus 5 | $0.00008 | $0.00528 |
| Sonnet 5 | $0.00003 | $0.00211 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade B, and why
containerization scanned grade B with 1 finding 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 4d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
- **Never run as root**: `USER 1000` in Dockerfile How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: containerization
Cursor Agent-Requested Rule — applied when AI determines relevance.
Containerization - Docker & Kubernetes
Build once, run anywhere. Container best practices for production workloads.
Docker Best Practices
Dockerfile Principles
# ✅ GOOD — Multi-stage build, minimal final image
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build
FROM node:18-alpine
RUN apk add --no-cache dumb-init
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/node_modules ./node_modules
EXPOSE 3000
USER node
CMD ["dumb-init", "node", "dist/main.js"]
# ❌ BAD — Single stage, large image, running as root
FROM node:18
COPY . .
RUN npm install
CMD ["node", "server.js"]
Image Optimization
| Technique | Benefit |
|---|---|
| Multi-stage builds | Smaller final image, no build tools in production |
| Alpine/slim base | Reduce image size by 50-90% |
| Layer caching | Order Dockerfile by change frequency |
| .dockerignore | Exclude node_modules, .git, logs |
| Non-root user | Security: RUN adduser -D appuser |
Kubernetes Patterns
Pod Design
apiVersion: v1
kind: Pod
metadata:
name: web-app
spec:
containers:
- name: app
image: myapp:v1.2.3
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
livenessProbe:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /ready
port: 8080
initialDelaySeconds: 5
periodSeconds: 5
Deployment Strategy
| Strategy | Use Case | Downtime |
|---|---|---|
| Rolling Update | Default, gradual replacement | Zero |
| Recreate | Complete replacement, simple | Yes |
| Blue-Green | Instant switch, easy rollback | Zero |
| Canary | Test with subset of traffic | Zero |
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.
- 4d ago First seen · 196 lines · 15 tokens per session scan B 1d6afc3a2c8d
containerization is a cursor rule published in the GitHub repository MN-Lizard-Team/aiyu-multi-agent (7 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 1,057 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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