best-practices/BESTPRACTICES.md

Best Practices Index

Generalised best practices extracted from real project work via the /distill-best-practices skill. Each topic file is self-contained — read only the files relevant to the current project.

Topics

• Validation & Deployment — Validate locally, deploy once; full-chain testing; pre-flight checks; DB migration patterns; K8s constraint planning; deployment checklists; inert-by-default feature flags; integration failure categorisation; safe persistence pattern
• Security Architecture — Server boundary rule: no credential crosses to the client; proxy + identity mapping pattern; defense in depth; anti-patterns
• Secrets Management — SOPS + age, credential handling, file naming, encryption gotchas, .env source injection, URL-safe passwords, per-workload secret scoping
• Git & Source Control — Commit practices, GitOps workflows, remote conventions
• Kubernetes Patterns — Volume mounts, deployment strategies, naming, bootstrap ordering, ArgoCD SSA quirks, etcd tuning, Secret volume gotchas, probe timeouts, Kustomize overlay image overrides, PodSecurity for monitoring, Cilium entity identities
• Helm Charts — Schema validation, version verification, values structure
• Ansible — Inventory, templates, idempotency, credential safety
• Scripting — Shell conventions, verification scripts, idempotency, colour output
• Documentation Standards — CLAUDE.md, MEMORY.md, FUTURE.md, README.md structure and tiered memory
• Milestones & Reflections — Milestone workflow, verification, reflection process
• Debugging Methodology — Systematic diagnosis, full-chain testing, common pitfalls, DB schema verification after deploy
• Claude Code Skills — Skill authoring, context injection, tool restrictions, read-only review skills, formatter/hook separation
• Linting & Formatting — Tool choices per language, PostToolUse hook, pre-commit integration, formatter contract
• Spec-Driven Development — Spec structure, requirement numbering, test-first workflow, multi-model review, plan-first approach, agent prompt conventions, wave-based TDD dispatch
• Test-Driven Development — Edge case discovery, property-based testing, mutation testing, AI agent testing patterns, test architecture
• Networking & Infrastructure — nftables safety, systemd socket activation, Docker forwarding, TLS SNI vs Host header, wildcard certs
• Docker UID Matching — UID wrapper entrypoint for mounted volumes, gosu pattern, when to use vs K8s securityContext
• Database Selection — SQLite is not a production database; always use PostgreSQL for services with FQDNs, multiple consumers, or concurrent access
• Docker — gosu PID 1, GIT_SSH_COMMAND scope, slim image health checks, buildx local images, Compose networking/restart gotchas, volume paths, override merge behaviour, init script privilege order, payload size limits, bind-mount rm gotcha
• API Design — Transport security, auth (OAuth2/JWT/mTLS), versioning, pagination, error handling, idempotency, rate limiting, input validation, zero-trust patterns
• API Integration — Client-side third-party API integration: capability verification, app-layer compensation, git+SOPS polling sync, bidirectional SoR
• Octopus Process Templates — OCL syntax, step template references, channel scoping, parameters, versioning, Platform Hub patterns
• LLM Code Security — Security vulnerabilities in AI-generated code: injection flaws, hardcoded secrets, hallucinated packages, over-permissive defaults, IaC risks, crypto mistakes, operational vulnerabilities (idempotency, CI/CD integrity, supply chain provenance, concurrent access), review checklists
• CI Container Builds — Registry cache with inline metadata, buildx in DinD, layer ordering, pip caching, path filter gotchas, SHA tagging strategy, runtime-mounted directory triggers
• Agent Repos & Container Agents — Task submission, harnesses, monitoring, multi-model workflows, agent repo forks, workspace layout, artifact passing via git branches, read-only test protection, infrastructure failure modes, cost-effective model scope boundaries
• AI Parallel Agents — Parallel agent orchestration: multi-facet research dispatch, file contention, WebFetch limits, narrow reads, dataset-wide audits
• Python Patterns — Non-reentrant Lock deadlocks, Pydantic v2 extra='ignore' silent drops, subprocess routing callables for mocking, model_validator for cross-field validation