Deploying To Staging Environment logo

Deploying To Staging Environment

Organization
AgentWorkforce
deploying-to-staging-environment

Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions

Overview

PublisherAgentWorkforce
Repositoryrelay
Skill namedeploying-to-staging-environment
Stars
875
Forks
73
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AgentWorkforce on GitHub. Read the source before you install it.

Installation

Install the Deploying To Staging Environment AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AgentWorkforce/relay/tree/main/.claude/skills/deploying-to-staging-environment
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgentWorkforce/relay.git /tmp/relay
mkdir -p .claude/skills
cp -r /tmp/relay/.claude/skills/deploying-to-staging-environment .claude/skills/deploying-to-staging-environment
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deploying To Staging Environment in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deploying To Staging Environment on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deploying To Staging Environment is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deploying to Staging Environment

Overview

The staging environment deployment is a coordinated multi-repo process that synchronizes code across three repositories (relay, relay-dashboard, relay-cloud) and automatically triggers deployment via GitHub Actions. Staging deployments ensure feature verification before production while keeping main branch clean during development.

When to Use

  • Integrating features across repos - Multiple components depend on changes in different repos
  • Testing feature branches together - Verify feature branch changes don't break integration
  • Promoting main to staging - Standard sync to keep staging up-to-date with latest main
  • Verifying deployment readiness - Test infrastructure changes or deployment workflows
  • Cross-team coordination - Share feature branches for integration testing

When NOT to use:

  • Emergency hotfixes (use production deployment instead)
  • Single-repo changes only (push directly if not blocking other repos)
  • Testing without intent to deploy (use local environment instead)

Architecture

The staging deployment system consists of:

Three Repos (relay, relay-dashboard, relay-cloud)
    ↓
Staging Branches (synced via git push)
    ↓
relay-cloud staging push triggers GitHub Actions
    ↓
Deploy-Staging Workflow (deploy-staging.yml)
    ↓
Fly.io Staging Environment (agent-relay-staging)
    ↓
Automatic health check verification

Key details:

  • Each repo has independent staging branch
  • relay-cloud staging branch push triggers automatic deployment
  • Workflow accepts optional relay/dashboard branch overrides
  • Falls back to main if specified branch doesn't exist
  • Workspace image builds in parallel with API deployment

Quick Reference

Standard Workflow (All Repos)

bash
# 1. Create git worktree for staging work (BEST PRACTICE)
cd /data/repos/relay
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push

# 2. Push latest main to staging (fetch fresh)
git fetch origin main:main
git push origin main:staging

# 3. Or push current feature branch to staging (if desired)
git fetch origin feature/your-branch:feature/your-branch
git push origin feature/your-branch:staging

# 4. Clean up worktree
cd /data/repos/relay
git worktree remove .worktrees/staging-push

Relay-Dashboard

bash
cd /data/repos/relay-dashboard
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin main:main
git push origin main:staging
cd /data/repos/relay-dashboard
git worktree remove .worktrees/staging-push

Relay-Cloud (Triggers Deployment)

bash
cd /data/repos/relay-cloud
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin main:main
git push origin main:staging
# ⚠️ This push triggers deploy-staging.yml workflow
cd /data/repos/relay-cloud
git worktree remove .worktrees/staging-push

Implementation

Why Git Worktrees?

Git worktrees provide several benefits for staging workflows:

  1. Isolation - Work on staging without changing main working directory state
  2. Safety - Feature branch checked out in worktree won't affect your current work
  3. Cleanliness - No lingering state changes after pushing
  4. Best practice - Standard DevOps approach for multi-branch operations

Step-by-Step Deployment Process

Prerequisites
  • Access to all three repos with push permission
  • Current working directory: one of the repos
  • No uncommitted changes blocking worktree creation
Execute Staging Push Across All Repos

Step 1: Relay

bash
cd /data/repos/relay
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin main:main
git push origin main:staging
cd /data/repos/relay
git worktree remove .worktrees/staging-push

Expected output:

Updated 'main' to 'origin/main'
remote: Create pull request for staging...
To github.com:AgentWorkforce/relay.git
 [new branch]      main -> staging
or
 * [up-to-date]    main -> staging

Step 2: Relay-Dashboard

bash
cd /data/repos/relay-dashboard
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin main:main
git push origin main:staging
cd /data/repos/relay-dashboard
git worktree remove .worktrees/staging-push

Step 3: Relay-Cloud (Triggers Deployment)

bash
cd /data/repos/relay-cloud
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin main:main
git push origin main:staging
# Deployment starts automatically!
cd /data/repos/relay-cloud
git worktree remove .worktrees/staging-push
Verify Deployment

After pushing relay-cloud, GitHub Actions starts automatically:

  1. Watch workflow progress:

  2. Verify health check:

    • Workflow runs curl https://agent-relay-staging.fly.dev/health
    • Expected: 200 response within 150 seconds
    • Retries 30 times with 5-second intervals
  3. Check deployment summary:

    • Click workflow run
    • View "Deployment Summary" in step summary
    • Confirms deployment to agent-relay-staging

Pushing Feature Branches to Staging

Instead of main, push a specific feature branch:

bash
cd /data/repos/relay
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin feature/your-feature:feature/your-feature
git push origin feature/your-feature:staging
cd /data/repos/relay
git worktree remove .worktrees/staging-push

For relay-cloud with custom relay/dashboard branches:

The deploy-staging.yml workflow accepts optional inputs to specify exact branches:

bash
# Push relay-cloud staging (will trigger GitHub Actions with inputs)
cd /data/repos/relay-cloud
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git fetch origin feature/custom-branch:feature/custom-branch
git push origin feature/custom-branch:staging
cd /data/repos/relay-cloud
git worktree remove .worktrees/staging-push

Then manually trigger with specific branches:

Common Mistakes

MistakeProblemFix
Pushing from dirty working treeWorktree creation fails with errorCommit or stash changes before creating worktree
Forgetting to remove worktreeAccumulates worktree directoriesAlways run git worktree remove .worktrees/staging-push after pushing
Pushing staging without relay/dashboardDeployment uses outdated relay/dashboardCoordinate all three repos or use GitHub Actions inputs to override
Not fetching fresh refPushes stale local branch stateAlways git fetch origin branch:branch before pushing
Confusing staging branch directionPush main→staging, not staging→mainRemember: feature work → staging branch, for promotion/testing
Assuming all repos auto-syncrelay/dashboard changes don't auto-triggerOnly relay-cloud staging push triggers deployment
Not checking health statusDeployment may fail silentlyAlways verify workflow completes and health check passes
Creating worktrees in wrong directoryPath confusion for multiple reposEach repo is separate; create worktrees within that repo's .worktrees/

Workflow Details

deploy-staging.yml Behavior

Triggers:

  • Manual push to staging branch (automatic)
  • GitHub Actions workflow_dispatch (manual with optional inputs)

Optional Workflow Inputs:

  • relay_branch - Override which relay branch to deploy (defaults to current staging branch)
  • dashboard_branch - Override which relay-dashboard branch to deploy (defaults to current staging branch)
  • Falls back to main if specified branch doesn't exist in remote

Deployment Steps:

  1. Checkout relay-cloud repository
  2. Determine relay branch (input or current, fallback to main)
  3. Determine dashboard branch (input or current, fallback to main)
  4. Setup Fly CLI
  5. Deploy to Fly.io with flyctl deploy
  6. Verify health check endpoint
  7. Create deployment summary

Environment: staging (requires GitHub Actions environment secrets)

Deployment Success Criteria

✅ All checks passed:

  • "Deploy to Staging" job completes
  • "Build Staging Workspace" job completes
  • Health check succeeds (HTTP 200 from /health endpoint)
  • Deployment summary shows all expected values

❌ Deployment failed:

  • Workflow run shows red X
  • Check step that failed in workflow logs
  • Common failures: auth (secrets), health check timeout, Docker build error

Real-World Workflow

Scenario: Feature across all three repos ready for integration testing

bash
# 1. Ensure local main branches are up-to-date
cd /data/repos/relay
git fetch origin main

cd /data/repos/relay-dashboard
git fetch origin main

cd /data/repos/relay-cloud
git fetch origin main

# 2. Push relay main to staging (using worktree)
cd /data/repos/relay
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git push origin main:staging
cd ..
git worktree remove .worktrees/staging-push

# 3. Push relay-dashboard main to staging
cd /data/repos/relay-dashboard
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git push origin main:staging
cd ..
git worktree remove .worktrees/staging-push

# 4. Push relay-cloud main to staging (triggers deployment)
cd /data/repos/relay-cloud
git worktree add .worktrees/staging-push main
cd .worktrees/staging-push
git push origin main:staging
cd ..
git worktree remove .worktrees/staging-push

# 5. Monitor deployment
echo "Check: https://github.com/AgentWorkforce/relay-cloud/actions"
# Wait for "Deploy (Staging)" workflow to complete
# Verify health check passes
# Access staging at: https://agent-relay-staging.fly.dev

Troubleshooting

Worktree Errors

Error: "fatal: 'main' already exists"

Solution: git worktree remove .worktrees/staging-push
         (if worktree from previous run still exists)

Error: "fatal: cannot checkout branch into locked working tree"

Solution: Ensure main branch isn't checked out in primary working tree
         git status (confirm different branch is checked out)

Deployment Failures

Health check timeout after 150s

Problem: Staging environment took too long to become healthy
Solution: - Check Fly.io logs: flyctl logs --app agent-relay-staging
         - Restart app: flyctl restart --app agent-relay-staging
         - Check for build errors in workflow logs
         - Look for startup errors in deployment step

Docker build fails

Problem: "Build Staging Workspace" job failed
Solution: - Check docker-staging.yml workflow logs
         - Verify Dockerfile exists and is valid
         - Check for resource/dependency issues
         - Rebuild locally to verify docker configuration

Branch not found fallback to main

Problem: Workflow says "using main" for your custom branch
Reason: Specified branch doesn't exist in relay/relay-dashboard
Solution: - Verify branch name is exact (case-sensitive)
         - Ensure branch exists in remote (git ls-remote origin)
         - Use GitHub Actions workflow_dispatch with correct inputs

Dependencies & Requirements

Git: Worktree feature (Git 2.5+, standard on all modern systems)

Permissions: Push access to all three repos:

  • github.com:AgentWorkforce/relay
  • github.com:AgentWorkforce/relay-dashboard
  • github.com:AgentWorkforce/relay-cloud

GitHub Secrets (relay-cloud):

  • CROSS_REPO_TOKEN - PAT with repo access across all three repos
  • FLY_API_TOKEN or FLY_API_TOKEN_STAGING - Fly.io deployment token

Environment: staging (configured in relay-cloud)


Key Principle: Use git worktrees for clean, isolated branch operations. Push coordination across repos, with relay-cloud staging push triggering automatic deployment.

Frequently asked questions

What does the Deploying To Staging Environment AI skill do?

Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions

Why use Deploying To Staging Environment on TypingMind?

Because you install it once and use it with any model. Deploying To Staging Environment is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deploying To Staging Environment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgentWorkforce/relay/tree/main/.claude/skills/deploying-to-staging-environment. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deploying To Staging Environment?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deploying To Staging Environment?

As many as you like. As long as a model supports skills, you can use Deploying To Staging Environment with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deploying To Staging Environment AI skill free?

Yes. It is published on GitHub by AgentWorkforce under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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