agentleFS
Sign inStart free
MrCipherSmithMrCipherSmith/goodai-base/skills/deploy/SKILL.md

deploy

Skill0 starsChanged 5 months agoMITView on GitHub

Use when deploying to any environment (staging, production) or when a deployment pipeline needs to run.

  • Installs packages

155 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use pm-discovery, qa-phase and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ww-w-aiSkill

    pm-discovery

    PM Agent Team - Automated product discovery, strategy, and PRD generation. Runs PM analysis workflow to produce comprehensive PRD before PDCA Plan phase.

    Also in 3 projects that use this

  • ww-w-aiSkill

    qa-phase

    Run QA tests at various levels (L1-L5) for features under PDCA management. Integrates with MCP tools to execute structured test plans.

    Also in 3 projects that use this

  • +10 more from ww-w-ai

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 139 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read package.json, docker-compose.yml, Dockerfile, vercel.json, railway.json, ecosystem.config.js, Makefile

    line 33
  2. Distinctive:

    Run in parallel where possible:

    line 39
  3. Distinctive:

    If any check fails → stop and report.

    line 47
  4. Distinctive:

    Check logs for startup errors

    line 61
  5. Distinctive:

    ALWAYS require explicit confirmation for production deploys

    line 66
  6. Very specific:

    NEVER deploy with failing tests (unless --skip-tests)

    line 67
  7. Distinctive:

    NEVER deploy from dirty working tree without warning

    line 68
  8. Distinctive:

    If deploy target can't be detected, ask the user

    line 70

“Common” is measured: kept by at least 6 in 10 of the 139 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Deploy

Automated deployment pipeline with pre-flight checks.

Arguments

  • /deploy — deploy to staging (default)
  • /deploy production — deploy to production (requires confirmation)
  • /deploy --skip-tests — skip test phase
  • /deploy --dry-run — show what would happen without executing
  • /deploy <env> --rollback — rollback to previous version

Workflow

Phase 1: Detect Project Type & Deploy Target

  1. Read package.json, docker-compose.yml, Dockerfile, vercel.json, railway.json, ecosystem.config.js, Makefile
  2. Detect stack: Node/Bun/Python/Go/Docker
  3. Detect deploy target: Docker Compose, PM2, SSH, Vercel, Railway, custom script
  4. Determine environment from argument (default: staging)

Phase 2: Pre-flight Checks

Run in parallel where possible:

  1. Git status: working tree clean (warn if dirty)
  2. Branch check: correct branch for target env (production → main/master)
  3. Tests: npm test / pytest / go test ./... (skip with --skip-tests)
  4. Lint: npm run lint if available
  5. Type-check: npx tsc --noEmit if TypeScript
  6. Build: npm run build / docker build

If any check fails → stop and report.

Phase 3: Deploy

TargetCommand
Docker Composedocker compose build && docker compose up -d
PM2pm2 reload ecosystem.config.js --env <env>
SSHssh <host> "cd <path> && git pull && npm install && npm run build && pm2 reload all"
Vercelvercel --prod or vercel (preview)
Customnpm run deploy:<env> or make deploy

Phase 4: Post-deploy Verification

  1. Health check: curl the health endpoint
  2. Check logs for startup errors
  3. Report: deployed version, environment, status

Rules

  • ALWAYS require explicit confirmation for production deploys
  • NEVER deploy with failing tests (unless --skip-tests)
  • NEVER deploy from dirty working tree without warning
  • Show summary before deploying: branch, env, target, version
  • If deploy target can't be detected, ask the user

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free