deployment-patterns

A set of procedures for managing a GitHub repository through the gh command-line tool. It covers issues, pull requests, automated checks, releases, contributors, and security alerts.

In plain words
What is it for?
Use it to triage issues, review or prepare pull requests, investigate CI failures, manage releases, monitor Dependabot alerts, and support contributors.
Why use it?
It turns recurring repository maintenance into a consistent process and helps keep work, checks, and community requests organised.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/chadixearth/graphyloop/deployment-patterns
Any agent
npx skills add chadixearth/graphyloop --skill deployment-patterns
Clone the repo
git clone --depth 1 https://github.com/chadixearth/graphyloop

Made for: Claude Code, Codex.

Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,181 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00031 $0.03181
Opus 5 $0.00015 $0.01590
Sonnet 5 $0.00006 $0.00636
Haiku 4.5 $0.00003 $0.00318

Measured 2d ago against content hash 0574363afba8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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
Origin

This is a copy

86% identical to deployment-patterns — 68 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/deployment-patterns/SKILL.md · 461 lines

How it starts

The opening of the file, as written. The whole thing — 461 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"]

Read the full file on GitHub · 461 lines

Changes

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.

  1. 2d ago First seen · 461 lines · 31 tokens per session scan A 0574363afba8

Subscribe to this mod's changes

deployment-patterns is a skill published in the GitHub repository chadixearth/graphyloop (2 stars, last pushed 16d ago), licensed MIT. It adds 31 tokens to every session and 3,181 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 86% identical to deployment-patterns, differing in 68 lines, and is treated as a copy.