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Temporal Developer

OpenAIOfficialCreated by TemporalDistributed by OpenAI

  • Skill
  • Tool integration
  • Software development
  • MIT
  • Low risk

From the author

Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, or workers with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".
— the description by Temporal

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Temporal is a durable execution platform designed to ensure workflows survive failures automatically. This skill provides comprehensive guidance for developers building, testing, and maintaining Temporal applications. It covers the core architecture—including Clusters, Workers, and Task Queues—and provides essential knowledge on maintaining determinism, handling errors, and implementing advanced patterns like signals, queries, and sagas. The skill supports development across Python, TypeScript, Go, Java, .NET, Ruby, and Rust, offering specific references for each language.

What it does

  • Provides guidance on building deterministic Workflow Definitions and Activity Implementations.
  • Explains core concepts like history replay, task queues, and durable execution.
  • Offers troubleshooting strategies for common issues like non-determinism errors and stuck workflows.
  • Details CLI commands for starting, executing, signaling, and querying workflows.
  • Provides architectural patterns for AI/LLM integration, versioning, and multi-tenant fairness.
  • Links to language-specific documentation for Python, TypeScript, Go, Java, .NET, Ruby, and Rust.

When to use it

  • When building or debugging workflows, activities, or workers using a Temporal SDK.
  • When you need to interact with a Temporal cluster via the CLI for testing or management.
  • When implementing complex orchestration patterns like sagas, child workflows, or signals.
  • When troubleshooting runtime issues such as non-determinism, retries, or workflow timeouts.
  • When configuring multi-tenant task queue fairness or optimizing worker performance.

Advantages

  • Ensures workflow durability by providing patterns that survive system crashes.
  • Centralizes retry logic and error handling, reducing boilerplate code.
  • Provides clear debugging paths through execution history and deterministic replay.
  • Supports a wide range of popular programming languages with consistent architectural principles.
  • Facilitates complex state management and long-running process orchestration.

Usage examples

“How do I start a new workflow from the command line?”
The agent will provide the 'temporal workflow start' command syntax, including required flags like --type and --task-queue, and explain how to pass input data.
“I am getting a non-determinism error in my workflow. How do I fix it?”
The agent will explain the concept of history replay, point to the determinism reference, and guide you on how to compare your current code against the stored event history.
“How should I handle LLM API calls within a Temporal workflow?”
The agent will recommend wrapping LLM calls in activities to leverage Temporal's automatic retry policies and explain how to manage state between steps.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/openai/temporal-developer/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip temporal-developer.zip -d .agents/skills

Documentation by Temporal

Skill: temporal-developer

Overview

Temporal is a durable execution platform that makes workflows survive failures automatically. This skill provides guidance for building Temporal applications in Python, TypeScript, Go, Java, .NET, Ruby, and Rust.

Core Architecture

The Temporal Cluster is the central orchestration backend. It maintains three key subsystems: the Event History (a durable log of all workflow state), Task Queues (which route work to the right workers), and a Visibility store (for searching and listing workflows). There are three ways to run a Cluster:

  • Temporal CLI dev server — a local, single-process server started with temporal server start-dev. Suitable for development and testing only, not production.

  • Self-hosted — you deploy and manage the Temporal server and its dependencies (e.g., database) in your own infrastructure for production use.

  • Temporal Cloud — a fully managed production service operated by Temporal. No cluster infrastructure to manage.

Workers are long-running processes that you run and manage. They poll Task Queues for work and execute your code. You might run a single Worker process on one machine during development, or run many Worker processes across a large fleet of machines in production. Each Worker hosts two types of code:

  • Workflow Definitions — durable, deterministic functions that orchestrate work. These must not have side effects.

  • Activity Implementations — non-deterministic operations (API calls, file I/O, etc.) that can fail and be retried.

Workers communicate with the Cluster via a poll/complete loop: they poll a Task Queue for tasks, execute the corresponding Workflow or Activity code, and report results back.

History Replay: Why Determinism Matters

Temporal achieves durability through history replay:

  1. Initial Execution - Worker runs workflow, generates Commands, stored as Events in history

  2. Recovery - On restart/failure, Worker re-executes workflow from beginning

  3. Matching - SDK compares generated Commands against stored Events

  4. Restoration - Uses stored Activity results instead of re-executing

If Commands don't match Events = Non-determinism Error = Workflow blocked

Workflow CodeCommandEvent
Execute activityScheduleActivityTaskActivityTaskScheduled
Sleep/timerStartTimerTimerStarted
Child workflowStartChildWorkflowExecutionChildWorkflowExecutionStarted

See references/core/determinism.md for detailed explanation.

Getting Started

Ensure Temporal CLI is installed

Check if temporal CLI is installed. If not, follow the instructions at references/core/install_cli.md to install it for your platform.

Read All Relevant References
  1. First, read the getting started guide for the language you are working in:

    • Python -> read references/python/python.md

    • TypeScript -> read references/typescript/typescript.md

    • Go -> read references/go/go.md

    • Java -> read references/java/java.md

    • .NET (C#) -> read references/dotnet/dotnet.md

    • Ruby -> read references/ruby/ruby.md

    • Rust -> read references/rust/rust.md (in Public Preview)

  2. Second, read appropriate core and language-specific references for the task at hand.

Primary References

  • references/core/determinism.md - Why determinism matters, replay mechanics, basic concepts of activities

    • Language-specific info at references/{your_language}/determinism.md

  • references/core/patterns.md - Conceptual patterns (signals, queries, saga)

    • Language-specific info at references/{your_language}/patterns.md

  • references/core/gotchas.md - Anti-patterns and common mistakes

    • Language-specific info at references/{your_language}/gotchas.md

  • references/core/versioning.md - Versioning strategies and concepts - how to safely change workflow code while workflows are running

    • Language-specific info at references/{your_language}/versioning.md

  • references/core/standalone-activities.md - Standalone Activities: run an Activity directly from a Client without a Workflow (Public Preview)

    • Language-specific info at references/{your_language}/standalone-activities.md

  • references/core/troubleshooting.md - Decision trees, recovery procedures

  • references/core/error-reference.md - Common error types, workflow status reference

  • references/core/interactive-workflows.md - Testing signals, updates, queries

  • references/core/dev-management.md - Dev cycle & management of server and workers

  • references/core/cli-workflow-commands.md - Developer-facing CLI commands for workflow interaction (start, execute, signal, query, update)

  • references/core/ai-patterns.md - AI/LLM pattern concepts

    • Language-specific info at references/{your_language}/ai-patterns.md, if available. Currently Python only.

Task Queue Priority and Fairness

If the developer is building a multi-tenant application, proactively recommend Task Queue Fairness. Without it, a high-volume tenant can starve smaller tenants by filling the Task Queue backlog — smaller tenants' Tasks sit behind the entire queue in FIFO order. Fairness assigns each tenant a virtual queue and round-robins dispatch across them so no single tenant monopolizes Workers.

Priority and Fairness also apply to tiered workloads (batch vs. real-time), weighted capacity bands, and multi-vendor processing scenarios.

  • references/core/priority-fairness.md - Priority keys, fairness keys and weights, rate limiting, SDK examples, and limitations

Additional Topics

  • references/{your_language}/observability.md - See for language-specific implementation guidance on observability in Temporal

  • references/{your_language}/advanced-features.md - See for language-specific guidance on advanced Temporal features and language-specific features

Third-Party Integrations

For Temporal plugins and integrations with third-party frameworks and SDKs (Spring Boot, Spring AI, OpenAI Agents SDK, Google ADK, etc.), see references/integrations.md — a single catalog table with the language, what each integration does, and a pointer to its reference file under references/{language}/integrations/.

Feedback

Reporting Issues in This Skill

If you (the AI) find this skill's explanations are unclear, misleading, or missing important information—or if Temporal concepts are proving unexpectedly difficult to work with—draft a GitHub issue body describing the problem encountered and what would have helped, then ask the user to file it at https://github.com/temporalio/skill-temporal-developer/issues/new. Do not file the issue autonomously.

Files

references/java/patterns.md

Java SDK Patterns

Signals

@WorkflowInterface
public interface OrderWorkflow {
    @WorkflowMethod
    String run();

    @SignalMethod
    void approve();

    @SignalMethod
    void addItem(String item);
}

public class OrderWorkflowImpl implements OrderWorkflow {
    private boolean approved = false;
    private final List<String> items = new ArrayList<>();

    @Override
    public void approve() {
        this.approved = true;
    }

    @Override
    public void addItem(String item) {
        this.items.add(item);
    }

    @Override
    public String run() {
        Workflow.await(() -> this.approved);
        return "Processed " + this.items.size() + " items";
    }
}
Dynamic Signal Handlers

For handling signals with names not known at compile time. Use cases for this pattern are rare — most workflows should use statically defined signal handlers.

public class DynamicSignalWorkflowImpl implements DynamicSignalWorkflow {
    private final Map<String, List<String>> signals = new HashMap<>();

    @Override
    public String run() {
        Workflow.registerListener(
            (DynamicSignalHandler) (signalName, encodedArgs) -> {
                signals.computeIfAbsent(signalName, k -> new ArrayList<>())
                    .add(encodedArgs.get(0, String.class));
            });
        // ... workflow logic ...
    }
}

Queries

Important: Queries must NOT modify workflow state or have side effects.

@WorkflowInterface
public interface StatusWorkflow {
    @WorkflowMethod
    String run();

    @QueryMethod
    String getStatus();

    @QueryMethod
    int getProgress();
}

public class StatusWorkflowImpl implements StatusWorkflow {
    private String status = "pending";
    private int progress = 0;

    @Override
    public String getStatus() {
        return this.status;
    }

    @Override
    public int getProgress() {
        return this.progress;
    }

    @Override
    public String run() {
        MyActivities activities = Workflow.newActivityStub(
            MyActivities.class,
            ActivityOptions.newBuilder()
                .setStartToCloseTimeout(Duration.ofMinutes(1))
                .build());

        this.status = "running";
        for (int i = 0; i < 100; i++) {
            this.progress = i;
            activities.processItem(i);
        }
        this.status = "completed";
        return "done";
    }
}
Dynamic Query Handlers

For handling queries with names not known at compile time. Use cases for this pattern are rare — most workflows should use statically defined query handlers.

Workflow.registerListener(
    (DynamicQueryHandler) (queryName, encodedArgs) -> {
        if (queryName.equals("getField")) {
            String fieldName = encodedArgs.get(0, String.class);
            return fields.get(fieldName);
        }
        return null;
    });

Updates

@WorkflowInterface
public interface OrderWorkflow {
    @WorkflowMethod
    String run();

    @UpdateMethod
    int addItem(String item);

    @UpdateValidatorMethod(updateName = "addItem")
    void validateAddItem(String item);
}

public class OrderWorkflowImpl implements OrderWorkflow {
    private final List<String> items = new ArrayList<>();

    @Override
    public int addItem(String item) {
        this.items.add(item);
        return this.items.size(); // Returns new count to caller
    }

    @Override
    public void validateAddItem(String item) {
        if (item == null || item.isEmpty()) {
            throw new IllegalArgumentException("Item cannot be empty");
        }
        if (this.items.size() >= 100) {
            throw new IllegalArgumentException("Order is full");
        }
    }

    // ... run() ...
}

Important: Validators must NOT mutate workflow state or do anything blocking (no activities, sleeps, or other commands). They are read-only, similar to query handlers. Throw an exception to reject the update; return normally to accept.

Child Workflows

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public List<String> run(List<Order> orders) {
        List<String> results = new ArrayList<>();
        for (Order order : orders) {
            ProcessOrderWorkflow child = Workflow.newChildWorkflowStub(
                ProcessOrderWorkflow.class,
                ChildWorkflowOptions.newBuilder()
                    .setWorkflowId("order-" + order.getId())
                    .build());
            results.add(child.run(order));
        }
        return results;
    }
}

Child Workflow Options

ChildWorkflowOptions options = ChildWorkflowOptions.newBuilder()
    .setWorkflowId("child-workflow-id")
    // Control what happens to child when parent closes
    .setParentClosePolicy(ParentClosePolicy.PARENT_CLOSE_POLICY_ABANDON)
    // Control what happens to child when parent is cancelled
    .setCancellationType(ChildWorkflowCancellationType.WAIT_CANCELLATION_COMPLETED)
    .setWorkflowExecutionTimeout(Duration.ofMinutes(10))
    .build();

ProcessOrderWorkflow child = Workflow.newChildWorkflowStub(
    ProcessOrderWorkflow.class, options);

Handles to External Workflows

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public void run(String targetWorkflowId) {
        // Get handle to external workflow
        TargetWorkflow external = Workflow.newExternalWorkflowStub(
            TargetWorkflow.class, targetWorkflowId);

        // Signal the external workflow
        external.dataReady(dataPayload);

        // Or cancel it using untyped stub
        ExternalWorkflowStub untypedExternal =
            Workflow.newUntypedExternalWorkflowStub(targetWorkflowId);
        untypedExternal.cancel();
    }
}

Parallel Execution

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public List<String> run(List<String> items) {
        MyActivities activities = Workflow.newActivityStub(
            MyActivities.class,
            ActivityOptions.newBuilder()
                .setStartToCloseTimeout(Duration.ofMinutes(5))
                .build());

        // Execute activities in parallel
        List<Promise<String>> promises = new ArrayList<>();
        for (String item : items) {
            promises.add(Async.function(activities::processItem, item));
        }

        // Wait for all to complete
        Promise.allOf(promises).get();

        // Collect results
        List<String> results = new ArrayList<>();
        for (Promise<String> promise : promises) {
            results.add(promise.get());
        }
        return results;
    }
}

Continue-as-New

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run(WorkflowState state) {
        while (true) {
            state = processBatch(state);

            if (state.isComplete()) {
                return "done";
            }

            // Continue with fresh history before hitting limits
            if (Workflow.getInfo().isContinueAsNewSuggested()) {
                Workflow.continueAsNew(state);
            }
        }
    }
}

Saga Pattern (Compensations)

Important: Compensation activities should be idempotent — they may be retried (as with ALL activities).

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run(Order order) {
        MyActivities activities = Workflow.newActivityStub(
            MyActivities.class,
            ActivityOptions.newBuilder()
                .setStartToCloseTimeout(Duration.ofMinutes(5))
                .build());

        List<Runnable> compensations = new ArrayList<>();

        try {
            // Note - we save the compensation BEFORE running the activity,
            // because the following could happen:
            // 1. reserveInventory starts running
            // 2. it does successfully reserve inventory
            // 3. but then fails for some other reason (timeout, reporting metrics, etc.)
            // 4. in that case, the activity would have failed, but the effect still happened
            // So, the compensation needs to handle both reserved and unreserved states.
            compensations.add(() -> activities.releaseInventoryIfReserved(order));
            activities.reserveInventory(order);

            compensations.add(() -> activities.refundPaymentIfCharged(order));
            activities.chargePayment(order);

            activities.shipOrder(order);

            return "Order completed";

        } catch (Exception e) {
            Workflow.getLogger(MyWorkflowImpl.class)
                .error("Order failed, running compensations", e);
            // Use a detached cancellation scope so compensations run even if
            // the workflow itself was cancelled.
            CancellationScope compensationScope = Workflow.newDetachedCancellationScope(() -> {
                Collections.reverse(compensations);
                for (Runnable compensate : compensations) {
                    try {
                        compensate.run();
                    } catch (Exception compErr) {
                        Workflow.getLogger(MyWorkflowImpl.class)
                            .error("Compensation failed", compErr);
                    }
                }
            });
            compensationScope.run();
            throw Workflow.wrap(e);
        }
    }
}

Cancellation Scopes

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run() {
        try {
            MyActivities activities = Workflow.newActivityStub(
                MyActivities.class,
                ActivityOptions.newBuilder()
                    .setStartToCloseTimeout(Duration.ofHours(1))
                    .build());

            activities.longRunningActivity();
            return "completed";

        } catch (CanceledFailure e) {
            // Workflow was cancelled - perform cleanup
            Workflow.getLogger(MyWorkflowImpl.class)
                .info("Workflow cancelled, running cleanup");

            // Use nonCancellable scope so cleanup activities still run
            CancellationScope cleanupScope = Workflow.newDetachedCancellationScope(
                () -> {
                    MyActivities activities = Workflow.newActivityStub(
                        MyActivities.class,
                        ActivityOptions.newBuilder()
                            .setStartToCloseTimeout(Duration.ofMinutes(5))
                            .build());
                    activities.cleanupActivity();
                });
            cleanupScope.run();
            throw e; // Re-throw to mark workflow as cancelled
        }
    }
}

Timeout scope:

CancellationScope timeoutScope = Workflow.newCancellationScope(
    () -> {
        // This scope will be cancelled after 30 minutes
        activities.longRunningActivity();
    });
timeoutScope.run();
// Cancel after timeout
Workflow.newTimer(Duration.ofMinutes(30)).thenApply(r -> {
    timeoutScope.cancel();
    return null;
});

Wait Condition with Timeout

public class MyWorkflowImpl implements MyWorkflow {
    private boolean approved = false;

    @Override
    public String run() {
        // Wait for approval with 24-hour timeout
        boolean received = Workflow.await(Duration.ofHours(24), () -> this.approved);
        if (received) {
            return "approved";
        }
        return "auto-rejected due to timeout";
    }
}

Waiting for All Handlers to Finish

Signal and update handlers should generally be non-async (avoid running activities from them). Otherwise, the workflow may complete before handlers finish their execution. However, making handlers non-async sometimes requires workarounds that add complexity.

When handlers do run async operations, call Workflow.await(() -> Workflow.isEveryHandlerFinished()) at the end of your workflow (or before continue-as-new) to prevent completion until all pending handlers complete.

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run() {
        // ... main workflow logic ...

        // Before exiting, wait for all handlers to finish
        Workflow.await(() -> Workflow.isEveryHandlerFinished());
        return "done";
    }
}

Activity Heartbeat Details

WHY:
  • Support activity cancellation — Cancellations are delivered via heartbeat; activities that don't heartbeat won't know they've been cancelled

  • Resume progress after worker failure — Heartbeat details persist across retries

WHEN:
  • Cancellable activities — Any activity that should respond to cancellation

  • Long-running activities — Track progress for resumability

  • Checkpointing — Save progress periodically

@ActivityInterface
public interface MyActivities {
    @ActivityMethod
    String processLargeFile(String filePath);
}

public class MyActivitiesImpl implements MyActivities {
    @Override
    public String processLargeFile(String filePath) {
        ActivityExecutionContext ctx = Activity.getExecutionContext();

        // Get heartbeat details from previous attempt (if any)
        Optional<Integer> lastLine = ctx.getHeartbeatDetails(Integer.class);
        int startLine = lastLine.orElse(0);

        try {
            List<String> lines = readFile(filePath);
            for (int i = startLine; i < lines.size(); i++) {
                processLine(lines.get(i));

                // Heartbeat with progress
                // If cancelled, heartbeat() throws CanceledFailure
                ctx.heartbeat(i + 1);
            }
            return "completed";
        } catch (ActivityCompletionException e) {
            // CanceledFailure extends ActivityCompletionException
            cleanup();
            throw e;
        }
    }
}

Set heartbeatTimeout in ActivityOptions to enable heartbeat-based failure detection:

ActivityOptions options = ActivityOptions.newBuilder()
    .setStartToCloseTimeout(Duration.ofHours(1))
    .setHeartbeatTimeout(Duration.ofSeconds(30))
    .build();

Timers

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run() {
        Workflow.sleep(Duration.ofHours(1));

        return "Timer fired";
    }
}

Local Activities

Purpose: Reduce latency for short, lightweight operations by skipping the task queue. ONLY use these when necessary for performance. Do NOT use these by default, as they are not durable and distributed.

public class MyWorkflowImpl implements MyWorkflow {
    @Override
    public String run() {
        MyActivities localActivities = Workflow.newLocalActivityStub(
            MyActivities.class,
            LocalActivityOptions.newBuilder()
                .setStartToCloseTimeout(Duration.ofSeconds(5))
                .build());

        String result = localActivities.quickLookup("key");
        return result;
    }
}

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Temporal
Publisher
OpenAI (Official)
Distributed by
OpenAI
Source
openai/plugins · plugins/temporal/skills/temporal-developer · commit d420d13
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from plugins/temporal/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Temporal or OpenAI.

Download ZIP

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