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ivklgnivklgn/ai-kit/skills/12-factor-apps/SKILL.md

12-factor-apps

Skill12 starsChanged 2 months agoMITView on GitHub

Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.

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We split this skill into the rules it gives an agent

11 rules. About 0 are common, 11 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈11

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

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  • Distinctive
  • Very specific
  1. Distinctive:

    No virtual environment or container isolation

    line 98
  2. Distinctive:

    Principle: Treat backing services as attached resources.

    line 143
  3. Distinctive:

    No PORT environment variable support

    line 279
  4. Distinctive:

    No separation between web and background processes

    line 314
  5. Distinctive:

    No SIGTERM/SIGINT handlers

    line 347
  6. Distinctive:

    No cleanup on shutdown

    line 350
  7. Distinctive:

    Principle: Keep development, staging, and production as similar as possible.

    line 356
  8. Distinctive:

    Principle: Treat logs as event streams.

    line 391
  9. Distinctive:

    Principle: Run admin/management tasks as one-off processes.

    line 426
  10. Distinctive:

    Run search patterns for all factors

    line 505
  11. Distinctive:

    Document evidence with file paths

    line 512

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

12-Factor App Compliance Analysis

Source & attribution. Ported from the 12-factor-apps skill by anderskev, published on clawhub.ai (https://clawhub.ai/anderskev/12-factor-apps), released under MIT-0. Methodology: The Twelve-Factor App by Adam Wiggins. See ATTRIBUTION.md.

Overview

The 12-Factor App methodology is a set of best practices for building Software-as-a-Service applications that are:

  • Portable across execution environments
  • Scalable without architectural changes
  • Suitable for continuous deployment
  • Maintainable with minimal friction

Input Parameters

ParameterDescriptionRequired
codebase_pathRoot path of the codebase to analyzeRequired

Analysis Framework

Factor I: Codebase

Principle: One codebase tracked in revision control, many deploys.

Search Patterns:

# Check for version control
ls -la .git 2>/dev/null || ls -la .hg 2>/dev/null

# Check for multiple apps sharing codebase
find . -name "package.json" -o -name "pyproject.toml" -o -name "setup.py" | head -20

# Check for environment-specific code branches
grep -r "if.*production\|if.*development\|if.*staging" --include="*.py" --include="*.js" --include="*.ts"

File Patterns: .git/, package.json, pyproject.toml, deployment configs

Compliance Criteria:

LevelCriteria
StrongSingle Git repo, same codebase for all environments, no env-specific code branches
PartialSingle repo but some environment-specific code paths
WeakMultiple repos for same app or significant code duplication across environments

Anti-patterns:

  • Multiple Git repositories for the same application
  • Environment-specific code branches (if production: ...)
  • Different source files for dev vs prod
  • Shared code not extracted to libraries

Factor II: Dependencies

Principle: Explicitly declare and isolate dependencies.

Search Patterns:

# Python dependency files
find . -name "requirements.txt" -o -name "pyproject.toml" -o -name "setup.py" -o -name "Pipfile" -o -name "uv.lock"

# JavaScript/TypeScript dependency files
find . -name "package.json" -o -name "package-lock.json" -o -name "yarn.lock" -o -name "pnpm-lock.yaml"

# Check for system tool assumptions
grep -r "subprocess.*curl\|subprocess.*wget\|os.system.*ffmpeg\|shutil.which" --include="*.py"
grep -r "exec.*curl\|child_process.*curl" --include="*.js" --include="*.ts"

# Docker/container isolation
find . -name "Dockerfile" -o -name "docker-compose*.yml"

File Patterns: **/requirements*.txt, **/package.json, **/*.lock, **/Dockerfile

Compliance Criteria:

LevelCriteria
StrongLock files present, dependency isolation (venv/Docker), no implicit system tools
PartialDependencies declared but no lock files or isolation
WeakDependencies in documentation only, relies on system-installed packages

Anti-patterns:

  • Missing lock files (non-deterministic builds)
  • Assuming system tools (curl, ImageMagick, ffmpeg) are available
  • Different dependency managers in dev vs production
  • No virtual environment or container isolation

Factor III: Config

Principle: Store config in the environment.

Search Patterns:

# Environment variable usage
grep -r "os.environ\|os.getenv\|process.env\|ENV\[" --include="*.py" --include="*.js" --include="*.ts" --include="*.rb"

# Hardcoded credentials (anti-pattern)
grep -r "password.*=.*['\"]" --include="*.py" --include="*.js" --include="*.ts" | grep -v "test\|spec\|example"
grep -r "api_key.*=.*['\"]" --include="*.py" --include="*.js" --include="*.ts" | grep -v "test\|spec\|example"
grep -r "secret.*=.*['\"]" --include="*.py" --include="*.js" --include="*.ts" | grep -v "test\|spec\|example"

# Environment-specific config files (anti-pattern)
find . -name "config.dev.*" -o -name "config.prod.*" -o -name "settings.development.*" -o -name "settings.production.*"

# Database URLs in code
grep -r "postgresql://\|mysql://\|mongodb://\|redis://" --include="*.py" --include="*.js" --include="*.ts" | grep -v ".env\|test\|example"

File Patterns: **/.env*, **/config/*.py, **/settings.py, environment files

Compliance Criteria:

LevelCriteria
StrongAll config via environment variables, no hardcoded secrets, could open-source without leaks
PartialMost config externalized but some hardcoded defaults
WeakHardcoded credentials, environment-specific config files

Anti-patterns:

  • Hardcoded database URLs, API keys, passwords in source
  • Config files like config/production.yml vs config/development.yml
  • Environment grouping (if ENV == 'production': ...)
  • Secrets committed to version control

Factor IV: Backing Services

Principle: Treat backing services as attached resources.

Search Patterns:

# Database connection via config
grep -r "DATABASE_URL\|DB_HOST\|REDIS_URL\|CACHE_URL" --include="*.py" --include="*.js" --include="*.ts"

# Service initialization
grep -r "create_engine\|MongoClient\|Redis\|Celery\|boto3" --include="*.py"
grep -r "createPool\|createClient\|new Redis\|S3Client" --include="*.js" --include="*.ts"

# Hardcoded service locations (anti-pattern)
grep -r "localhost:5432\|localhost:6379\|localhost:27017\|127.0.0.1" --include="*.py" --include="*.js" --include="*.ts" | grep -v "test\|spec\|example\|default"

File Patterns: **/database/*.py, **/services/*.py, **/db.py, connection configurations

Compliance Criteria:

LevelCriteria
StrongAll services via URL/connection string in config, swappable without code changes
PartialMost services configurable but some hardcoded defaults
WeakHardcoded service locations, different code paths per environment

Anti-patterns:

  • Hardcoded localhost for services in production code
  • Conditional logic for local vs cloud services (if USE_S3: ... else: local_storage)
  • Service-specific code paths based on environment
  • Different drivers for dev vs prod

Factor V: Build, Release, Run

Principle: Strictly separate build and run stages.

Search Patterns:

# Build/deploy configuration
find . -name "Dockerfile" -o -name "Makefile" -o -name "build.sh" -o -name "deploy.sh"
find . -name ".github/workflows/*.yml" -o -name ".gitlab-ci.yml" -o -name "Jenkinsfile"

# Build scripts in package.json
grep -A5 '"scripts"' package.json 2>/dev/null | grep -E "build|start|deploy"

# Check for runtime compilation (anti-pattern)
grep -r "compile\|transpile\|webpack" --include="*.py" | grep -v "test\|build"

File Patterns: **/Dockerfile, **/Makefile, **/.github/workflows/**, CI/CD configs

Compliance Criteria:

LevelCriteria
StrongImmutable releases, clear build/release/run stages, unique release IDs
PartialBuild and run separated but release not immutable
WeakRuntime code modifications, asset compilation at startup

Anti-patterns:

  • Runtime code modifications
  • Asset compilation during application startup
  • Configuration baked into build artifacts
  • No release versioning

Factor VI: Processes

Principle: Execute the app as one or more stateless processes.

Search Patterns:

# Session storage patterns
grep -r "session\|Session" --include="*.py" --include="*.js" --include="*.ts" | head -20

# In-process state (anti-pattern)
grep -r "global.*cache\|process_local\|instance_cache" --include="*.py"
grep -r "global\..*=\|module\.exports\.cache" --include="*.js" --include="*.ts"

# External session stores (good pattern)
grep -r "redis.*session\|memcached.*session\|session.*redis" --include="*.py" --include="*.js" --include="*.ts"

# Sticky session configuration (anti-pattern)
grep -r "sticky.*session\|session.*affinity" --include="*.yml" --include="*.yaml" --include="*.json"

File Patterns: **/middleware/*.py, **/session/*.py, server configurations

Compliance Criteria:

LevelCriteria
StrongStateless processes, all state in external datastores (Redis, DB)
PartialMostly stateless but some in-process caching
WeakSticky sessions, in-process session storage, shared memory state

Anti-patterns:

  • In-process session storage (user_sessions = {})
  • Sticky sessions or session affinity
  • File-based caching between requests
  • Global mutable state shared across requests

Factor VII: Port Binding

Principle: Export services via port binding.

Search Patterns:

# Self-contained port binding
grep -r "app.run\|server.listen\|serve\|uvicorn" --include="*.py"
grep -r "app.listen\|server.listen\|createServer" --include="*.js" --include="*.ts"

# PORT environment variable
grep -r "PORT\|port" --include="*.py" --include="*.js" --include="*.ts" | grep -i "environ\|process.env"

# Webserver as dependency
grep -r "uvicorn\|gunicorn\|flask\|fastapi\|express\|koa\|hapi" package.json pyproject.toml requirements.txt 2>/dev/null

File Patterns: **/main.py, **/server.py, **/app.py, **/index.js

Compliance Criteria:

LevelCriteria
StrongSelf-contained app binds to PORT, webserver is a dependency
PartialPort binding but not configurable via environment
WeakRelies on external webserver container (Apache, Nginx) to provide HTTP

Anti-patterns:

  • Relying on Apache/Nginx/Tomcat to inject webserver functionality
  • Hardcoded port numbers
  • No PORT environment variable support
  • CGI scripts or server modules

Factor VIII: Concurrency

Principle: Scale out via the process model.

Search Patterns:

# Process definitions
find . -name "Procfile" -o -name "process.yml" -o -name ".foreman"

# Multiple entry points
find . -name "worker.py" -o -name "scheduler.py" -o -name "web.py"

# Background job systems
grep -r "celery\|rq\|sidekiq\|bull\|agenda" --include="*.py" --include="*.js" --include="*.ts"
grep -r "Celery\|Worker\|BackgroundJob" --include="*.py" --include="*.js" --include="*.ts"

File Patterns: **/Procfile, **/worker.py, **/scheduler.py, queue configurations

Compliance Criteria:

LevelCriteria
StrongExplicit process types (web, worker, scheduler), horizontal scaling
PartialMultiple process types but not easily scalable
WeakSingle monolithic process, no separation of concerns

Anti-patterns:

  • Single process handling all workloads
  • Hard-coded worker counts in code
  • No separation between web and background processes
  • Vertical scaling only (bigger server, not more processes)

Factor IX: Disposability

Principle: Maximize robustness with fast startup and graceful shutdown.

Search Patterns:

# Signal handlers
grep -r "signal.signal\|SIGTERM\|SIGINT\|atexit" --include="*.py"
grep -r "process.on.*SIGTERM\|process.on.*SIGINT" --include="*.js" --include="*.ts"

# Graceful shutdown
grep -r "graceful.*shutdown\|shutdown_handler\|cleanup" --include="*.py" --include="*.js" --include="*.ts"

# Startup time
grep -r "startup\|initialize\|bootstrap" --include="*.py" --include="*.js" --include="*.ts" | head -20

File Patterns: **/main.py, **/server.py, lifecycle management code

Compliance Criteria:

LevelCriteria
StrongFast startup (<10s), SIGTERM handling, graceful shutdown, jobs returnable to queue
PartialGraceful shutdown but slow startup
WeakNo signal handling, jobs lost on process death, slow startup

Anti-patterns:

  • No SIGTERM/SIGINT handlers
  • Slow startup (>30 seconds)
  • Jobs lost if process crashes
  • No cleanup on shutdown

Factor X: Dev/Prod Parity

Principle: Keep development, staging, and production as similar as possible.

Search Patterns:

# Different services per environment (anti-pattern)
grep -r "if.*development.*sqlite\|if.*production.*postgres" --include="*.py" --include="*.js" --include="*.ts"
grep -r "development.*SQLite\|production.*PostgreSQL" --include="*.py" --include="*.js" --include="*.ts"

# Docker for parity
find . -name "docker-compose*.yml" -o -name "Dockerfile"

# Environment-specific backends
grep -r "USE_LOCAL_\|LOCAL_STORAGE\|MOCK_" --include="*.py" --include="*.js" --include="*.ts"

File Patterns: **/docker-compose*.yml, environment configurations

Compliance Criteria:

LevelCriteria
StrongSame services everywhere (PostgreSQL in dev and prod), containerized
PartialMostly same but some lightweight dev alternatives
WeakSQLite in dev, PostgreSQL in prod; different backing services

Anti-patterns:

  • SQLite for development, PostgreSQL for production
  • In-memory cache in dev, Redis in prod
  • Different service versions across environments
  • "It works on my machine" issues

Factor XI: Logs

Principle: Treat logs as event streams.

Search Patterns:

# Stdout logging
grep -r "print(\|logging.info\|logger.info\|console.log" --include="*.py" --include="*.js" --include="*.ts" | head -20

# File-based logging (anti-pattern)
grep -r "FileHandler\|open.*\.log\|writeFile.*log\|fs.appendFile.*log" --include="*.py" --include="*.js" --include="*.ts"
grep -r "/var/log\|/tmp/.*\.log\|logs/" --include="*.py" --include="*.js" --include="*.ts" | grep -v "test\|example"

# Structured logging
grep -r "structlog\|json_logger\|pino\|winston" --include="*.py" --include="*.js" --include="*.ts"

File Patterns: **/logging.py, **/logger.py, logging configurations

Compliance Criteria:

LevelCriteria
StrongUnbuffered stdout only, structured logging (JSON), no file management
PartialStdout logging but with some file handlers
WeakApplication writes to log files, manages rotation

Anti-patterns:

  • Writing logs to files (FileHandler, open('/var/log/app.log'))
  • Log rotation logic in application code
  • Log archival managed by application
  • Buffered logging

Factor XII: Admin Processes

Principle: Run admin/management tasks as one-off processes.

Search Patterns:

# Management commands
find . -name "manage.py" -o -name "Rakefile" -o -name "artisan"
grep -r "@cli.command\|@click.command\|typer.command" --include="*.py"

# Migration scripts
find . -name "migrations" -type d
find . -name "*migration*.py" -o -name "*migrate*.py"

# Admin scripts with proper isolation
grep -r "bundle exec\|source.*venv\|uv run" --include="*.sh" --include="Makefile"

File Patterns: **/manage.py, **/cli.py, **/migrations/**, admin scripts

Compliance Criteria:

LevelCriteria
StrongAdmin tasks use same dependencies/config, proper isolation, idempotent
PartialAdmin tasks exist but different setup from app
WeakManual database manipulation, scripts without isolation

Anti-patterns:

  • Admin scripts not using app's dependency manager
  • Direct SQL manipulation outside of migrations
  • Admin scripts with hardcoded credentials
  • Non-idempotent migrations

Output Format

Executive Summary Table

| Factor | Status | Notes |
|--------|--------|-------|
| I. Codebase | **Strong/Partial/Weak** | [Key finding] |
| II. Dependencies | **Strong/Partial/Weak** | [Key finding] |
| III. Config | **Strong/Partial/Weak** | [Key finding] |
| IV. Backing Services | **Strong/Partial/Weak** | [Key finding] |
| V. Build/Release/Run | **Strong/Partial/Weak** | [Key finding] |
| VI. Processes | **Strong/Partial/Weak** | [Key finding] |
| VII. Port Binding | **Strong/Partial/Weak** | [Key finding] |
| VIII. Concurrency | **Strong/Partial/Weak** | [Key finding] |
| IX. Disposability | **Strong/Partial/Weak** | [Key finding] |
| X. Dev/Prod Parity | **Strong/Partial/Weak** | [Key finding] |
| XI. Logs | **Strong/Partial/Weak** | [Key finding] |
| XII. Admin Processes | **Strong/Partial/Weak** | [Key finding] |

**Overall**: X Strong, Y Partial, Z Weak

Per-Factor Analysis

For each factor, provide:

  1. Current Implementation
    • Evidence with file:line references
    • Code snippets showing patterns
  2. Compliance Level
    • Strong/Partial/Weak with justification
  3. Gaps
    • What's missing vs. 12-Factor ideal
  4. Recommendations
    • Actionable improvements with code examples

Analysis Workflow

  1. Initial Scan
    • Run search patterns for all factors
    • Identify key files for each factor
    • Note any existing compliance documentation
  2. Deep Dive (per factor)
    • Read identified files
    • Evaluate against compliance criteria
    • Document evidence with file paths
  3. Gap Analysis
    • Compare current vs. 12-Factor ideal
    • Identify anti-patterns present
    • Prioritize by impact
  4. Recommendations
    • Provide actionable improvements
    • Include before/after code examples
    • Reference best practices
  5. Summary
    • Compile executive summary table
    • Highlight strengths and critical gaps
    • Suggest priority order for improvements

Quick Reference: Compliance Scoring

ScoreMeaningAction
StrongFully implements principleMaintain, minor optimizations
PartialSome implementation, significant gapsPlanned improvements
WeakMinimal or no implementationHigh priority for roadmap

When to Use This Skill

  • Evaluating new SaaS applications
  • Reviewing cloud-native architecture decisions
  • Auditing production applications for scalability
  • Planning migration to cloud platforms
  • Comparing application architectures
  • Preparing for containerization/Kubernetes deployment

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