minimal-build

# Minimal Build Skill Implement features with absolute minimum code for Python, Kubernetes, AWS. ## Prime Directive **Every line is a liability.** Delete before adding. Reuse before writing. Configure before coding. ## Decision Hierarchy ### 1. DELETE First - Remove dead code, unused dependencies - Simplify requirements to avoid code ### 2. CONFIGURE Second - Use existing CLI flags, env vars - Leverage tool defaults ### 3. REUSE Third - Standard library over dependencies - Existing project code over new ### 4. WRITE Last (minimal) - One-liners over functions - Functions over classes - Composition over inheritance ## Python Minimalism ### DO ```python # Use stdlib from pathlib import Path # not os.path from dataclasses import dataclass # not manual __init__ from functools import lru_cache # not manual caching # Use comprehensions items = [x for x in data if x.valid] # not loops # Use context managers with open(f) as f: ... # not try/finally ``` ### DON'T ```python # Don't add utils.py with one function # Don't create abstract base classes for one implementation # Don't add type hints for obvious types # Don't wrap stdlib in "helper" classes ``` ### Prefer - `uv` by default. Use Poetry only if the repo already requires it. - `ruff` over flake8+black+isort (one tool) - `pytest` over unittest (less boilerplate) - `httpx` over requests (async-ready, modern) - `pydantic` for validation (not manual checks) ## Kubernetes Minimalism ### DO ```yaml # Use Deployment defaults # Don't specify what matches defaults spec: replicas: 1 # only if not default # Use Kustomize over Helm for simple cases # Use ConfigMaps for config, not env vars sprawl ``` ### DON'T ```yaml # Don't create CRDs for simple config # Don't add operators when Jobs suffice # Don't use Helm for < 5 manifests # Don't create namespaces per-microservice ``` ### Prefer - `kubectl apply -k` over Helm for simple deploys - `Deployment` over `StatefulSet` unless you need stable identity - `Job` over custom controllers for batch work - `ConfigMap` over Secrets for non-sensitive config ## AWS Minimalism ### DO ```python # Use boto3 defaults client = boto3.client('s3') # not custom sessions for basic use # Use managed services # Lambda > ECS > EKS for simple workloads ``` ### DON'T ```python # Don't wrap boto3 in abstraction layers # Don't create custom retry logic (use botocore) # Don't build what AWS provides (SQS > custom queue) ``` ### Prefer - SSM Parameter Store over custom config - Lambda over containers for event-driven - S3 events over polling - SQS/SNS over custom messaging - CloudFormation/CDK outputs over hardcoded ARNs ## Output Format ``` Lines added: X Lines removed: Y Dependencies: [added/removed] K8s resources: [added/removed] AWS resources: [added/removed] ``` ## Anti-patterns - "We might need scaling" -> Start with 1 replica - "Let me add monitoring" -> Use managed (CloudWatch, Prometheus operator) - "Custom logging framework" -> Use stdlib logging + structured output - "Wrapper around boto3" -> Just use boto3 directly