Production Stack Skills

Turn your coding agent into a senior production engineer.
Skill pack for FastAPI, PostgreSQL, Docker, deployment, and observability — works with Claude Code, Codex, and any AGENTS.md-compatible agent CLI.

Install · Commands · Skills · /production check · Architecture

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Why This Exists

Stop shipping demo-quality code. AI generates code fast — this skill pack makes it generate code that survives production.

Metric	Source
45% of AI-generated code has security vulnerabilities	State of Software Delivery 2025
67% of developers spend MORE time debugging AI code	Developer Survey 2025
78% of Fortune 500 companies are adopting AI coding	Enterprise AI Report 2026

The gap between "it works" and "it survives Black Friday at 3 AM" is what this skill pack closes.

Every Claude Code skill teaches how to build something. None teach how to make it survive production. Missing health checks, unsafe migrations, root containers, no graceful shutdown — these are the things that page you at 3 AM.

production-stack-skills is the senior engineer sitting next to you that catches these issues before they ship.

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🚀 Quick Start

One-Command Install (macOS & Linux)

curl -fsSL https://raw.githubusercontent.com/vstorm-co/production-stack-skills/main/install.sh | bash

The installer mirrors skills into both ~/.claude/ and ~/.agents/ — so the same install works with Claude Code, Codex, or any AGENTS.md-compatible agent CLI without extra steps.

Manual Install

git clone https://github.com/vstorm-co/production-stack-skills.git
cd production-stack-skills
./install.sh

Requirements

• An agent CLI — Claude Code, Codex, or any AGENTS.md-compatible agent
• Python 3.10+ — for audit scripts
• Git — for cloning

Uninstall

curl -fsSL https://raw.githubusercontent.com/vstorm-co/production-stack-skills/main/uninstall.sh | bash

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🧰 Commands

Command	What It Does
/production check	Full audit with 0-100 score and prioritized action plan
/production score	Quick 60-second headline score
/production fastapi	Apply FastAPI production patterns
/production postgres	Safe migrations, pooling, indexes
/production docker	Multi-stage builds, non-root, minimal images
/production deploy	Pre-deployment checklist
/production monitoring	OTEL traces, structured logging, metrics, alerts
/production security	Secrets, CORS, auth, rate limiting, OWASP checks
/production errors	Error taxonomy, retries, circuit breakers
/production review	Production-readiness code review
/production plan	Architecture planning with production constraints
/production report	Shareable Markdown readiness report

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🎯 The /production check Experience

The flagship command. Scans your entire project across six categories and scores it 0-100:

## Production Readiness Audit

Project: my-fastapi-app
Stack: Python 3.12 / FastAPI 0.115 / PostgreSQL 16 / Docker
Score: 34/100 — Grade F

| Category                    | Score  | Weight | Weighted |
|-----------------------------|--------|--------|----------|
| Security Fundamentals       | 40/100 | 25%    | 10       |
| Error Handling & Resilience | 25/100 | 20%    | 5        |
| Observability               | 20/100 | 20%    | 4        |
| Deployment Readiness        | 50/100 | 15%    | 7.5      |
| Database Patterns           | 60/100 | 10%    | 6        |
| Container Hygiene           | 15/100 | 10%    | 1.5      |
| Total                       |        |        | 34/100   |

Quick Wins (< 5 minutes each):
  [+12 pts] Replace print() with structlog
  [+8 pts]  Add /health/live and /health/ready endpoints
  [+6 pts]  Add USER directive to Dockerfile
  [+4 pts]  Add .dockerignore

Fix these 4 items → score jumps from 34 to ~64.

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📚 Skills

Skill	What It Teaches	Works With
production-check	Full audit with 0-100 scoring, parallel analysis, prioritized action plan	Any stack
production-review	Production-readiness code review — security, errors, logging, config, performance	Python, Node.js, Go, Java
production-planner	Architecture planning with scalability, failure modes, cost constraints	Any stack
production-fastapi	Lifespan, ASGI middleware, structured logging, health checks, Pydantic v2, async	Python / FastAPI
production-postgres	Zero-downtime migrations, indexing strategies, connection pooling, schema design	PostgreSQL
production-docker	Multi-stage builds, non-root, distroless, BuildKit secrets, security scanning	Docker / OCI
production-deploy	Pre-deployment checklist, migration classification, rollback playbook, CI/CD	Any CI/CD
production-monitoring	OpenTelemetry, structlog, Prometheus metrics, health endpoints, SLO definition	Any stack (OTEL)
production-security	Secrets management, CORS, JWT, rate limiting, security headers, OWASP Top 10	Any stack
production-error-handling	Error taxonomy, retry with backoff, circuit breakers, graceful degradation, DLQ	Any stack

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🔗 How Skills Work Together

Skills trigger automatically based on context and reinforce each other:

"Create a FastAPI endpoint"
  → production-fastapi activates: structured logging, health checks, error handling

"Write a migration to add a NOT NULL column"
  → production-postgres activates: 3-step safe pattern, lock_timeout, rollback script

"Create a Dockerfile"
  → production-docker activates: multi-stage, non-root, distroless, HEALTHCHECK

"Is this production ready?"
  → production-check activates: full 6-category audit with score

After completing one skill, related skills are suggested:

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

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🏗 Architecture

production/SKILL.md              ← Orchestrator (routes /production subcommands)
│
├── skills/
│   ├── production-check/        ← Full audit with 0-100 scoring
│   ├── production-fastapi/      ← FastAPI production patterns
│   ├── production-postgres/     ← PostgreSQL safety & performance
│   ├── production-docker/       ← Container hardening
│   ├── production-deploy/       ← Pre-deployment validation
│   ├── production-monitoring/   ← Observability
│   ├── production-security/     ← Security hardening
│   ├── production-error-handling/ ← Resilience patterns
│   ├── production-review/       ← Code review
│   └── production-planner/      ← Architecture planning
│
├── agents/                      ← Parallel audit subagents
├── checklists/                  ← Reusable reference checklists
├── install.sh                   ← One-command installer
└── uninstall.sh

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🧭 Philosophy

1. Opinionated over generic — We recommend specific tools and patterns, not abstract advice
2. Production-proven — Every pattern comes from real incident post-mortems
3. Fail-safe defaults — When in doubt, the safer option wins
4. Progressive adoption — Each skill works alone; together they cover the full stack
5. LLM judges taste; scripts judge facts — Deterministic checks where possible, LLM judgment where needed

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Contributing

Pull requests welcome. Pattern to add new skills:

1. Create skill directory in skills/production-<name>/
2. Add SKILL.md with frontmatter (name, description) and content
3. Add to orchestrator router in production/SKILL.md
4. Add auditor in agents/ if parallel audit needed
5. Optional: templates in templates/, references in references/

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Vstorm OSS Ecosystem

production-stack-skills is part of a broader open-source ecosystem for production AI agents:

Project	Description
pydantic-deep	The batteries-included deep agent harness for Python. Terminal AI assistant or production agents with one function call.
full-stack-ai-agent-template	Zero to production AI app in 30 minutes. FastAPI + Next.js 15, 6 AI frameworks, RAG pipeline, 75+ config options.
content-skills	Claude Code content studio — blog, social, slides, video, infographics — all brand-aware.
pydantic-ai-shields	Drop-in guardrails for Pydantic AI agents. 5 infra + 5 content shields.
pydantic-ai-subagents	Declarative multi-agent orchestration with token tracking.
summarization-pydantic-ai	Smart context compression for long-running agents.
pydantic-ai-backend	Sandboxed execution for AI agents. Docker + Daytona.

Browse all projects at oss.vstorm.co

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License

MIT — see LICENSE

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Need help shipping production-grade backends?

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with 30+ production agent implementations. These patterns come from 50+ production deployments.

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