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/mturac/everything-openai-codex/deployment-patternsnpx skills add mturac/everything-openai-codex --skill deployment-patternsgit clone --depth 1 https://github.com/mturac/everything-openai-codexWhat 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 | $0.00041 | $0.02908 |
| Opus 5 | $0.00020 | $0.01454 |
| Sonnet 5 | $0.00008 | $0.00582 |
| Haiku 4.5 | $0.00004 | $0.00291 |
Grade A, and why
deployment-patterns scanned grade A 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1 Copies of this mod
8 near-identical copies found in the catalogue:
- deployment-patterns — 100% identical, 2 lines differ
- deployment-patterns — 100% identical, 2 lines differ
- deployment-patterns — 100% identical, 2 lines differ
- deployment-patterns — 100% identical, 2 lines differ
- deployment-patterns — 98% identical, 10 lines differ
- deployment-patterns — 97% identical, 16 lines differ
- deployment-patterns — 97% identical, 17 lines differ
- deployment-patterns — 97% identical, 17 lines differ
How it starts
The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Patterns
Production deployment workflows and CI/CD best practices.
When to Activate
- Setting up CI/CD pipelines
- Dockerizing an application
- Planning deployment strategy (blue-green, canary, rolling)
- Implementing health checks and readiness probes
- Preparing for a production release
- Configuring environment-specific settings
Deployment Strategies
Rolling Deployment (Default)
Replace instances gradually — old and new versions run simultaneously during rollout.
Instance 1: v1 → v2 (update first)
Instance 2: v1 (still running v1)
Instance 3: v1 (still running v1)
Instance 1: v2
Instance 2: v1 → v2 (update second)
Instance 3: v1
Instance 1: v2
Instance 2: v2
Instance 3: v1 → v2 (update last)
Pros: Zero downtime, gradual rollout Cons: Two versions run simultaneously — requires backward-compatible changes Use when: Standard deployments, backward-compatible changes
Blue-Green Deployment
Run two identical environments. Switch traffic atomically.
Blue (v1) ← traffic
Green (v2) idle, running new version
# After verification:
Blue (v1) idle (becomes standby)
Green (v2) ← traffic
Pros: Instant rollback (switch back to blue), clean cutover Cons: Requires 2x infrastructure during deployment Use when: Critical services, zero-tolerance for issues
Canary Deployment
Route a small percentage of traffic to the new version first.
v1: 95% of traffic
v2: 5% of traffic (canary)
# If metrics look good:
v1: 50% of traffic
v2: 50% of traffic
# Final:
v2: 100% of traffic
Pros: Catches issues with real traffic before full rollout Cons: Requires traffic splitting infrastructure, monitoring Use when: High-traffic services, risky changes, feature flags
Docker
Multi-Stage Dockerfile (Node.js)
# Stage 1: Install dependencies
FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production=false
# Stage 2: Build
FROM node:22-alpine AS builder
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
RUN npm run build
RUN npm prune --production
# Stage 3: Production image
FROM node:22-alpine AS runner
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001
USER appuser
COPY --from=builder --chown=appuser:appgroup /app/node_modules ./node_modules
COPY --from=builder --chown=appuser:appgroup /app/dist ./dist
COPY --from=builder --chown=appuser:appgroup /app/package.json ./
ENV NODE_ENV=production
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1
CMD ["node", "dist/server.js"]
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 · 441 lines · 41 tokens per session scan A d843b04a1b7a
deployment-patterns is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 8d ago), licensed MIT. It adds 41 tokens to every session and 2,908 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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