Oban job processing — workers, perform/1 (OSS) and process/1 (Pro), queues, cron, retries, unique jobs, idempotency, Oban Pro (Workflow, Batch, Chunk, Smart Engine), Testing. Use when writing Oban workers, queue config, or debugging jobs.
npx skills add https://github.com/oliver-kriska/claude-elixir-phoenix --skill oban
Quick reference for Elixir Oban patterns.
Before applying patterns, check for Oban Pro:
grep -E "oban_pro|oban_web" mix.exs
grep -r "use Oban.Pro.Worker" lib/
grep -r "Oban.Pro.Engines.Smart" config/
If Oban Pro detected, use Pro patterns for ALL new workers:
| Standard Oban | Oban Pro |
|---------------|----------|
| use Oban.Worker | use Oban.Pro.Worker |
| def perform(%Job{}) | def process(%Job{}) |
| Oban.Testing | Oban.Pro.Testing |
| Advisory lock engine | Oban.Pro.Engines.Smart |
Pro features (all optional): args_schema (typed args), Workflows, Batches, Chunks,
Relay, hooks, encryption, deadlines, chaining, Smart Engine (global concurrency + rate limiting).
Pro plugins (DynamicCron, DynamicLifeline, DynamicPruner) enhance OSS equivalents — swap module, don't run both.
See references/oban-pro-basics.md for all patterns and migration guide.
%{user_id: 1} not %{user: %User{}}:ok, {:error, _}, {:cancel, _}, {:snooze, _}%{"user_id" => id} not %{user_id: id}attempt TO LIMIT SNOOZES — Snooze rolls back attempt counter. Use meta["snoozed"] instead. Causes infinite loopsdefmodule MyApp.Workers.ExampleWorker do
use Oban.Worker,
queue: :default,
max_attempts: 5,
unique: [period: {5, :minutes}, keys: [:entity_id]]
@impl Oban.Worker
def perform(%Oban.Job{args: %{"entity_id" => id}}) do
case process(id) do
{:ok, _} -> :ok
{:error, :not_found} -> {:cancel, "Entity not found"}
{:error, :rate_limited} -> {:snooze, {5, :minutes}}
{:error, reason} -> {:error, reason}
end
end
end
| Return | State | Behavior |
|--------|-------|----------|
| :ok | completed | Success |
| {:ok, value} | completed | Success with value |
| {:error, reason} | retryable | Retry with backoff |
| {:cancel, reason} | cancelled | Stop permanently |
| {:snooze, seconds} | scheduled | Delay and retry |
dispatch_cooldown for rate limitinguse Oban.Testing, repo: MyApp.Repo
# Assert enqueued
assert_enqueued worker: MyApp.Worker, args: %{id: 1}
# Execute and verify
assert :ok = perform_job(MyApp.Worker, %{id: 1})
| Wrong | Right |
|-------|-------|
| %{user_id: id} pattern match | %{"user_id" => id} (string keys) |
| %{user: %User{}} in args | %{user_id: 1} (IDs only) |
| No idempotency for payments | Use idempotency keys |
| Ignoring return values | Handle all outcomes explicitly |
For detailed patterns, see:
references/worker-patterns.md - Worker options, backoff, timeoutreferences/queue-config.md - Queue design, pool sizing, cron, Smart Enginereferences/testing-patterns.md - Testing, assertions, drain (OSS + Pro)references/oban-pro-basics.md - Pro.Worker, Workflow, Batch, Chunk, Relay, pluginsToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take oliver-kriska/claude-elixir-phoenix-oban from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.