Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure.

MITAuto-check: notesDevOps & Cloud

Install Relay Deploy

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill relay-deploy -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace relay-deploy --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ai-agency/tonone/skills/relay-deploy .claude/skills/relay-deploy && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
relay-deploy
GitHub stars
2.8k
Token cost
~3k tokens
SKILL.md length
409 words
Files
2
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure.

  • Works in 7 steps: Read the Project → Pick the Deployment Strategy → Write the Dockerfile → …
  • Asked about deployment setup
  • SKILL.md covers Step 0: Read the Project, Step 1: Pick the Deployment…, Step 2: Write the Dockerfile and Step 3: Write the Deployment…, plus 4 more sections
  • Calls gcloud, kubectl and flyctl

What it does

Relay Deploy is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure. Use when asked about "deployment setup", "how do I deploy this", "deployment strategy", or "rollback plan".

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `.claude-plugin/plugin.json`).

It sits in DevOps & Cloud, covering Deployment and Containers. It works with Docker, Cloud Run and Kubernetes. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked about deployment setup
  • How do I deploy this
  • Deployment strategy

Example prompts

  • “deployment setup”
  • “how do I deploy this”
  • “deployment strategy”
  • “/relay-deploy”

Requirements

  • Python 3
  • Node.js
  • Docker
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Read the Project
  2. Pick the Deployment Strategy
  3. Write the Dockerfile
  4. Write the Deployment Manifest
  5. Write the Rollback Procedure
  6. Smoke Test Script
  7. Output

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep
    • WebFetch
    • WebSearch
    • Task
    • TodoWrite

    …and 1 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gcloud
    • kubectl
    • flyctl
    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gcloud, kubectl and curl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Relay Deploy loads about 3k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 409 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:119
    .env
  • NoteMentions a .env fileSKILL.md:120
    .env.*
  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 409 words, ~2,987 tokens.

Download SKILL.mdSave it as .claude/skills/relay-deploy/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
relay-deploy
description
Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure. Use when asked about "deployment setup", "how do I deploy this", "deployment strategy", or "rollback plan".
allowed-tools
Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion
version
0.6.4
author
tonone-ai <hello@tonone.ai>
license
MIT

Set Up Deployment Configuration

You are Relay — the DevOps engineer from the Engineering Team.

You write the deployment config. You don't present three strategies and ask the human to pick. Given a service description, you produce the Dockerfile (if needed), deployment manifest, environment config, and rollback procedure — ready to use.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Step 0: Read the Project

bash
ls -a
cat package.json 2>/dev/null | head -20 || cat pyproject.toml 2>/dev/null | head -20 || cat go.mod 2>/dev/null | head -5 || true
cat fly.toml 2>/dev/null || cat render.yaml 2>/dev/null || ls k8s/ 2>/dev/null || ls kubernetes/ 2>/dev/null || true
cat Dockerfile 2>/dev/null | head -10 || true

Determine:

  • Language and runtime — Node, Python, Go, Rust, Java
  • Service type — HTTP API, background worker, scheduled job, static site
  • Deployment target — Cloud Run, Fly.io, ECS, Kubernetes, Render, Railway, Vercel
  • Scale expectation — single instance, auto-scale, multi-region
  • Existing deploy config — Dockerfile, fly.toml, render.yaml, k8s manifests

Step 1: Pick the Deployment Strategy

Make the decision — don't ask:

ContextStrategy
Stateless HTTP service, most casesRolling — simple, zero config, safe for 90% of deploys
User-facing change with real blast radiusCanary — route 10% traffic to new revision, observe, promote
Database migration or schema changeBlue-green — two full environments, atomic traffic switch

Default: rolling. Canary and blue-green add complexity; only use them when the risk justifies it. On Cloud Run and Fly.io, rolling is native and requires no extra setup. Use canary when you have >1k DAU and a meaningful error rate baseline to compare against. Use blue-green when you have a migration that can't be rolled back easily.

Step 2: Write the Dockerfile

If no Dockerfile exists, write one. Multi-stage, minimal runtime image, non-root user.

Node.js (Next.js / Express)
dockerfile
FROM node:22.12-slim AS builder
WORKDIR /app
COPY package-lock.json package.json ./
RUN npm ci
COPY . .
RUN npm run build

FROM node:22.12-slim AS runner
WORKDIR /app
ENV NODE_ENV=production
RUN addgroup --system --gid 1001 nodejs && adduser --system --uid 1001 nextjs
COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static
COPY --from=builder --chown=nextjs:nodejs /app/public ./public
USER nextjs
EXPOSE 3000
CMD ["node", "server.js"]
Show full SKILL.md (163 more words)Show less
Python (FastAPI / Flask)
dockerfile
FROM python:3.12-slim AS builder
WORKDIR /app
RUN pip install uv
COPY pyproject.toml uv.lock ./
RUN uv sync --frozen --no-dev

FROM python:3.12-slim AS runner
WORKDIR /app
RUN addgroup --system --gid 1001 appgroup && adduser --system --uid 1001 appuser
COPY --from=builder --chown=appuser:appgroup /app/.venv ./.venv
COPY --chown=appuser:appgroup . .
USER appuser
EXPOSE 8000
ENV PATH="/app/.venv/bin:$PATH"
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
Go
dockerfile
FROM golang:1.23-alpine AS builder
WORKDIR /app
COPY go.mod go.sum ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 GOOS=linux go build -ldflags="-w -s" -o /app/server ./cmd/server

FROM scratch
COPY --from=builder /etc/ssl/certs/ca-certificates.crt /etc/ssl/certs/
COPY --from=builder /app/server /server
EXPOSE 8080
ENTRYPOINT ["/server"]
.dockerignore
.git
node_modules
.venv
__pycache__
*.pyc
target
.env
.env.*
.DS_Store
*.test
*.md
.github
.gitlab
docs
coverage

Step 3: Write the Deployment Manifest

Cloud Run (rolling — default)
yaml
# cloudrun-service.yaml
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: your-service # configure
  annotations:
    run.googleapis.com/ingress: all
spec:
  template:
    metadata:
      annotations:
        autoscaling.knative.dev/minScale: "1"
        autoscaling.knative.dev/maxScale: "10"
        run.googleapis.com/execution-environment: gen2
    spec:
      containerConcurrency: 80
      timeoutSeconds: 30
      serviceAccountName: your-sa@your-project.iam.gserviceaccount.com # configure
      containers:
        - image: us-central1-docker.pkg.dev/your-project/your-repo/your-service:latest
          ports:
            - containerPort: 8080
          resources:
            limits:
              cpu: "1"
              memory: 512Mi
          env:
            - name: NODE_ENV
              value: production
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: database-url # configure in Secret Manager
                  key: latest
          readinessProbe:
            httpGet:
              path: /health
            initialDelaySeconds: 5
            periodSeconds: 10
  traffic:
    - percent: 100
      latestRevision: true
Cloud Run — Canary (10% to new revision)
bash
# After deploying the new revision with --no-traffic:
gcloud run deploy your-service \
  --image IMAGE_URL \
  --no-traffic \
  --tag canary \
  --region us-central1

# Split traffic: 10% to canary, 90% to stable
gcloud run services update-traffic your-service \
  --to-tags canary=10,stable=90 \
  --region us-central1

# Promote to 100% after validation:
gcloud run services update-traffic your-service \
  --to-latest \
  --region us-central1
Fly.io (fly.toml)
toml
app = "your-app"         # configure
primary_region = "iad"   # configure

[build]

[http_service]
  internal_port = 8080
  force_https = true
  auto_stop_machines = "stop"
  auto_start_machines = true
  min_machines_running = 1

[[http_service.checks]]
  grace_period = "5s"
  interval = "10s"
  method = "GET"
  path = "/health"
  timeout = "2s"

[deploy]
  strategy = "rolling"

[[vm]]
  size = "shared-cpu-1x"
  memory = "512mb"
Kubernetes (rolling — deployment.yaml)
yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: your-service
  labels:
    app: your-service
spec:
  replicas: 2
  selector:
    matchLabels:
      app: your-service
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0 # zero-downtime: never kill old before new is ready
  template:
    metadata:
      labels:
        app: your-service
    spec:
      containers:
        - name: your-service
          image: your-registry/your-service:latest
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 500m
              memory: 512Mi
          readinessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 5
            failureThreshold: 3
          livenessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 15
            periodSeconds: 20
          env:
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: your-service-secrets
                  key: database-url

Step 4: Write the Rollback Procedure

Every deployment config ships with this. Rollback must execute in under 2 minutes.

Cloud Run rollback
bash
# List recent revisions
gcloud run revisions list --service your-service --region us-central1

# Route 100% traffic to the previous stable revision
gcloud run services update-traffic your-service \
  --to-revisions your-service-00042-abc=100 \
  --region us-central1

# Verify traffic is fully shifted
gcloud run services describe your-service --region us-central1 | grep traffic

Trigger when: error rate >1% sustained for 2 minutes, p99 latency >2s, smoke test failure.

Fly.io rollback
bash
# List recent releases
flyctl releases list

# Roll back to previous release
flyctl deploy --image registry.fly.io/your-app:deployment-XXXXXXXXXX

# Or use the image digest from `flyctl releases list`

Trigger when: health check failures, error spike in flyctl logs.

Kubernetes rollback
bash
# Check rollout status
kubectl rollout status deployment/your-service

# Roll back to previous version immediately
kubectl rollout undo deployment/your-service

# Roll back to a specific revision
kubectl rollout history deployment/your-service
kubectl rollout undo deployment/your-service --to-revision=3

# Verify pods are healthy
kubectl get pods -l app=your-service

Trigger when: pod crash loops, readiness probe failures, error spike in metrics.

Step 5: Smoke Test Script

bash
#!/usr/bin/env bash
# smoke-test.sh — run after every deploy
set -euo pipefail

BASE_URL="${1:-https://your-service.example.com}"
MAX_LATENCY_MS=500

echo "Running smoke tests against $BASE_URL..."

# Health check
STATUS=$(curl -s -o /dev/null -w "%{http_code}" "$BASE_URL/health")
[ "$STATUS" = "200" ] || { echo "FAIL: /health returned $STATUS"; exit 1; }

# Latency check
LATENCY=$(curl -s -o /dev/null -w "%{time_total}" "$BASE_URL/health")
LATENCY_MS=$(echo "$LATENCY * 1000" | bc | cut -d. -f1)
[ "$LATENCY_MS" -lt "$MAX_LATENCY_MS" ] || { echo "FAIL: /health latency ${LATENCY_MS}ms > ${MAX_LATENCY_MS}ms"; exit 1; }

# Version check (optional — requires /version or X-Version header)
# VERSION=$(curl -s "$BASE_URL/version" | jq -r .version)
# [ "$VERSION" = "$EXPECTED_VERSION" ] || { echo "FAIL: wrong version $VERSION"; exit 1; }

echo "OK: all smoke tests passed"

Step 6: Output

Write the files directly:

  • Dockerfile (if it didn't exist)
  • .dockerignore (if it didn't exist)
  • Deployment manifest (cloudrun-service.yaml, fly.toml, k8s/deployment.yaml, etc.)
  • scripts/smoke-test.sh

Then output a summary:

┌─ Deployment config written ─────────────────────────────────┐
│                                                              │
│  Strategy:   rolling (Cloud Run)                             │
│  Files:      Dockerfile                                      │
│              .dockerignore                                   │
│              cloudrun-service.yaml                           │
│              scripts/smoke-test.sh                           │
│                                                              │
│  Deploy:     gcloud run services replace cloudrun-service.yaml │
│  Rollback:   gcloud run services update-traffic ... (2 min)  │
│                                                              │
│  Secrets to configure (2):                                   │
│  □ DATABASE_URL — in Secret Manager as "database-url"        │
│  □ [any others]                                              │
│                                                              │
│  Smoke test: bash scripts/smoke-test.sh https://your-url     │
└──────────────────────────────────────────────────────────────┘

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/ai-agency/tonone/skills/relay-deploy of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • .claude-plugin/plugin.json

Open the folder on GitHubat commit cfae287

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LangBot Deployment Guidelangbot-app/LangBot18k—~1.2kAutomated safety check: NotesApache-2.0
Devopsnicepkg/auto-company1952 repos~814Automated safety check: PassMIT
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Categories

Questions about Relay Deploy

What does Relay Deploy do?

Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure. Relay Deploy is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure.

When should I use Relay Deploy?

Relay Deploy fits situations like: asked about deployment setup; how do I deploy this; deployment strategy.

How do I install Relay Deploy in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill relay-deploy -a claude-code`. Or copy the skill folder (plugins/ai-agency/tonone/skills/relay-deploy in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/relay-deploy in your project. Claude Code loads it when a task matches its description.

How do I install Relay Deploy in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill relay-deploy -a codex`. Or copy the skill folder (plugins/ai-agency/tonone/skills/relay-deploy in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/relay-deploy in your project. Codex loads it when a task matches its description.

Can I use Relay Deploy in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill relay-deploy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/relay-deploy, .gemini/skills/relay-deploy, .github/skills/relay-deploy and .opencode/skills/relay-deploy in your project.

What does Relay Deploy need to run?

Going by SKILL.md and its folder, Relay Deploy needs the command-line tools its instructions call (gcloud, kubectl, flyctl and curl). Our summary lists: Python 3; Node.js; Docker. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion.

Does Relay Deploy access the network?

SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Relay Deploy safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Relay Deploy use?

Relay Deploy is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Relay Deploy use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Relay Deploy?

Skills that share tags, products or a category with Relay Deploy: CI/CD Pipeline Principles (irahardianto/awesome-agv, 156 stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars), LangBot Deployment Guide (langbot-app/LangBot, 18k stars) and Devops (nicepkg/auto-company, 195 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Relay Deploy?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.