Use when preparing code for production, running mix precommit, mix compile warnings-as-errors, mix credo --strict, mix format, mix test failures, adding typespecs, evaluating security posture, checking migration safety, or reviewing code before committing
Enforces production readiness by running precommit checks, analyzing code quality, and ensuring security and observability standards.
/plugin marketplace add jeffweiss/elixir-production/plugin install elixir-production@jeffweissThis skill inherits all available tools. When active, it can use any tool Claude has access to.
configuration.mddatabase.mddeployment.mdecto-preloading.mderror-handling.mdescalation-ladder.mdobservability.mdproperty-based-testing.mdsecurity.mdtesting.mdProduction readiness is an escalation ladder — L0 (compiles) through L7 (documented). Most features should reach at least L3 before merge.
| Level | Gate | Command/Check |
|---|---|---|
| L0 | Compiles cleanly | mix compile --warnings-as-errors (includes set-theoretic type checks on 1.18+) |
| L1 | Formatted | mix format (with Styler) |
| L2 | Static analysis | mix credo --strict |
| L3 | Tested | mix test — all ok/error paths, edge cases |
| L4 | Typed | @spec on every public function, concrete types (compiler infers many types on 1.18+, specs remain valuable for API documentation) |
| L5 | Secure | OWASP defenses: parameterized queries, escaped output, changeset validation |
| L6 | Observable | Telemetry on all 4 layers (OS/VM, framework, app, user) |
| L7 | Documented | @moduledoc, @doc with examples, "why" comments |
Precommit gate (L0-L3 automated):
# mix.exs aliases
precommit: ["compile --warnings-as-errors", "deps.unlock --unused", "format", "credo --strict", "test"]
concurrently: true or multi-step deployment causes downtime{:error, _} branchRead the file that matches your current problem:
escalation-ladder.md — When: Need details on any production readiness level (L0-L7). Full Production Readiness Ladder (L0-L7 with code examples, gate criteria)testing.md — When: Designing test strategy or setting up TDD workflow. Testing strategy, TDD, error handling imperative, documentation standardsproperty-based-testing.md — When: Testing with StreamData generators or properties. StreamData generators, custom generators, property patterns (roundtrip, idempotency, oracle, metamorphic), shrinking, Ecto integrationsecurity.md — When: Hardening against injection, XSS, CSRF, or managing secrets. SQL injection, XSS, CSRF, input validation, secrets management, timing attacks, magic link authobservability.md — When: Adding telemetry, tracing, or alerting. Telemetry layers, span conventions, tracing-as-analytics, alerting, gray failures, degraded mode, process labelsdatabase.md — When: Writing migrations or tuning Ecto queries. Safe Ecto migrations, isolation level warnings, dependency SLAs, performance guidelinesecto-preloading.md — When: Fixing N+1 queries or choosing preload strategy. N+1 detection and prevention, preload strategies (join, subquery, inline), LiveView preloadingerror-handling.md — When: Designing error flows or debugging crash patterns. Crash early patterns, strict-then-loosen, complexity analysisdeployment.md — When: Building releases, health checks, or Docker configs. Mix releases, health checks (liveness/readiness), graceful shutdown, Docker, Fly.io/K8s patternsconfiguration.md — When: Choosing between compile-time and runtime config. config.exs vs runtime.exs, compile_env vs get_env, runtime secrets, config providers/precommit — Enforces L0-L3 automatically (compile, format, credo, test)/review [file] — Comprehensive review against L4-L7 standards/spike-migrate — Upgrade SPIKE code to production qualityActivates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.