Metadata

name: production
description: Main orchestrator for the production-stack-skills pack. Routes /production subcommands to specialized skills. Use this skill when the user types /production followed by a subcommand (check, fastapi, postgres, docker, deploy, monitoring, security, errors, report, score). Also triggers when user says 'make this production ready', 'productionize this', or asks about production readiness in general.

Production Stack Skills — Orchestrator

You are the router for the production-stack-skills pack. When the user invokes /production <subcommand>, dispatch to the appropriate specialized skill.

Command Router

Command	Skill	What It Does
`/production check`	production-check	Full audit with 0-100 score and prioritized action plan
`/production score`	production-check	Quick 60-second headline score, top 3 findings
`/production report`	production-check	Full audit formatted as a shareable Markdown report
`/production fastapi`	production-fastapi	Apply FastAPI production patterns to current project
`/production postgres`	production-postgres	Review migrations, indexes, connections, schema design
`/production docker`	production-docker	Audit or generate production-grade Dockerfile
`/production deploy`	production-deploy	Pre-deployment checklist walkthrough
`/production monitoring`	production-monitoring	Add OTEL traces, structured logging, health endpoints
`/production security`	production-security	Security audit — secrets, CORS, auth, rate limiting
`/production errors`	production-error-handling	Apply error handling patterns — retries, circuit breakers
`/production review`	production-review	Production-readiness code review on specific files/PRs
`/production plan`	production-planner	Architecture planning with production constraints

Routing Logic

Parse the subcommand from the user's input
Detect the project stack (language, framework, database, infrastructure)
Dispatch to the appropriate skill — load its SKILL.md and follow its instructions
If no subcommand is given, show the command table above and ask what they'd like to do
If the subcommand is ambiguous, ask for clarification

No Subcommand — Default Behavior

If the user just says /production without a subcommand, respond with:

Production Stack Skills — available commands:

  /production check       Full audit with 0-100 score
  /production score       Quick headline score (60 seconds)
  /production fastapi     FastAPI production patterns
  /production postgres    PostgreSQL safety & performance
  /production docker      Container hardening
  /production deploy      Pre-deployment checklist
  /production monitoring  Observability setup
  /production security    Security hardening
  /production errors      Error handling patterns
  /production review      Production-readiness code review
  /production plan        Architecture planning
  /production report      Shareable readiness report

What would you like to do?

Stack Detection

Before dispatching, detect the project stack to provide context to the sub-skill:

Check for:
├── Python:     pyproject.toml, requirements.txt, setup.py, Pipfile
│   ├── FastAPI:  "fastapi" in dependencies
│   ├── Django:   "django" in dependencies
│   └── Flask:    "flask" in dependencies
├── Node.js:    package.json
│   ├── Express:  "express" in dependencies
│   └── Fastify:  "fastify" in dependencies
├── Go:         go.mod
├── Java:       pom.xml, build.gradle
├── Database:   connection strings, ORM configs, migration directories
├── Docker:     Dockerfile, docker-compose.yml
└── CI/CD:      .github/workflows/, .gitlab-ci.yml

Pass the detected stack to the sub-skill so it can tailor its recommendations.

General Guidelines

When routing to a sub-skill:

Be specific: pass the detected stack and relevant file paths
Be efficient: don't re-detect what the sub-skill will detect
Be helpful: if the user asks for something that spans multiple skills, run them in sequence
Cross-reference: after completing one skill, suggest related skills that would help

Example: After /production fastapi, suggest:

"Your FastAPI patterns are solid. Consider running /production docker to harden your container, and /production check for a full audit."

production