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

Download the skill as a ZIP:
https://autogineer.com/agent-skills/openai/temporal-developer/download

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:

Initial Execution - Worker runs workflow, generates Commands, stored as Events in history
Recovery - On restart/failure, Worker re-executes workflow from beginning
Matching - SDK compares generated Commands against stored Events
Restoration - Uses stored Activity results instead of re-executing

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

Workflow Code	Command	Event
Execute activity	`ScheduleActivityTask`	`ActivityTaskScheduled`
Sleep/timer	`StartTimer`	`TimerStarted`
Child workflow	`StartChildWorkflowExecution`	`ChildWorkflowExecutionStarted`

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

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)
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

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references/typescript/typescript.md

Temporal TypeScript SDK Reference

Overview

The Temporal TypeScript SDK provides a modern Promise based approach to building durable workflows. Workflows are bundled and run in an isolated runtime with automatic replacements for determinism protection.

CRITICAL: All @temporalio/* packages must have the same version number.

Understanding Replay

Temporal workflows are durable through history replay. For details on how this works, see references/core/determinism.md.

Quick Start

Add Dependencies: Install the Temporal SDK packages (use the package manager appropriate for your project):

npm install @temporalio/client @temporalio/worker @temporalio/workflow @temporalio/activity @temporalio/envconfig

Note: if you are working in production, it is strongly advised to use ~ version constraints, i.e. npm install ... --save-prefix='~' if using NPM.

activities.ts - Activity definitions (separate file to distinguish workflow vs activity code):

export async function greet(name: string): Promise<string> {
  return `Hello, ${name}!`;
}

workflows.ts - Workflow definition (use type-only imports for activities):

import { proxyActivities } from '@temporalio/workflow';
import type * as activities from './activities';

const { greet } = proxyActivities<typeof activities>({
  startToCloseTimeout: '1 minute',
});

export async function greetingWorkflow(name: string): Promise<string> {
  return await greet(name);
}

worker.ts - Worker setup (registers activity and workflow, runs indefinitely and processes tasks):

import { NativeConnection, Worker } from '@temporalio/worker';
import { loadClientConnectConfig } from '@temporalio/envconfig';
import * as activities from './activities';

async function run() {
  const config = loadClientConnectConfig();
  const connection = await NativeConnection.connect(config.connectionOptions);
  const worker = await Worker.create({
    connection,
    namespace: config.namespace,
    workflowsPath: require.resolve('./workflows'), // For production, use workflowBundle instead
    activities,
    taskQueue: 'greeting-queue',
  });
  await worker.run();
}

run().catch(console.error);

Start the dev server: Start temporal server start-dev in the background.

Start the worker: Run npx ts-node worker.ts in the background.

client.ts - Start a workflow execution:

import { Client, Connection } from '@temporalio/client';
import { loadClientConnectConfig } from '@temporalio/envconfig';
import { greetingWorkflow } from './workflows';
import { v4 as uuid } from 'uuid';

async function run() {
  const config = loadClientConnectConfig();
  const connection = await Connection.connect(config.connectionOptions);
  const client = new Client({ connection, namespace: config.namespace });

  const result = await client.workflow.execute(greetingWorkflow, {
    workflowId: uuid(),
    taskQueue: 'greeting-queue',
    args: ['my name'],
  });

  console.log(`Result: ${result}`);
}

run().catch(console.error);

Run the workflow: Run npx ts-node client.ts. Should output: Result: Hello, my name!.

Key Concepts

Workflow Definition

Async functions exported from workflow file
Use proxyActivities() with type-only imports
Use defineSignal(), defineQuery(), defineUpdate(), setHandler() for handlers

Activity Definition

Regular async functions
Can perform I/O, network calls, etc.
Use heartbeat() for long operations

Worker Setup

Load connection settings with loadClientConnectConfig() and pass them to NativeConnection.connect()
Pass namespace: config.namespace to Worker.create() - NativeConnection carries no namespace, and the Worker defaults to default without it
Use Worker.create() with workflowsPath (dev) or workflowBundle (production) - see references/typescript/gotchas.md
Import activities directly (not via proxy)

File Organization Best Practice

Keep Workflow definitions in separate files from Activity definitions. The TypeScript SDK bundles workflow files separately. Minimizing workflow file contents improves Worker startup time.

my_temporal_app/
├── workflows/
│   └── greeting.ts      # Only Workflow functions
├── activities/
│   └── translate.ts     # Only Activity functions
├── worker.ts            # Worker setup, imports both
└── client.ts            # Client code to start workflows

In the Workflow file, use type-only imports for activities:

// workflows/greeting.ts
import { proxyActivities } from '@temporalio/workflow';
import type * as activities from '../activities/translate';

const { translate } = proxyActivities<typeof activities>({
  startToCloseTimeout: '1 minute',
});

Determinism Rules

The TypeScript SDK runs workflows in an isolated V8 sandbox.

Automatic replacements:

Math.random() → deterministic seeded PRNG
Date.now() → workflow start time
setTimeout → deterministic timer

Safe to use:

sleep() from @temporalio/workflow
condition() for waiting
Standard JavaScript operations

See references/typescript/determinism.md for detailed rules.

Common Pitfalls

Importing activities without type - Use import type * as activities
Version mismatch - All @temporalio packages must match
Direct I/O in workflows - Use activities for external calls
Missing proxyActivities - Required to call activities from workflows
Forgetting to bundle workflows - Worker needs workflowsPath or workflowBundle
Using workflowsPath in production - Use workflowBundle for production (see references/typescript/gotchas.md)
Forgetting to heartbeat - Long-running activities need heartbeat() calls
Logging in workflows - For observability, use import { log } from '@temporalio/workflow' (routes through sinks). For temporary print debugging, console.log() is fine—it's direct and immediate, whereas log may lose messages on workflow errors.
Forgetting to wait on activity calls - Activity calls return Promises; you must eventually await them (directly or via Promise.all() for parallel execution)

Writing Tests

See references/typescript/testing.md for info on writing tests.

Additional Resources

Reference Files

references/typescript/patterns.md - Signals, queries, child workflows, saga pattern, etc.
references/typescript/determinism.md - Essentials of determinism in TypeScript
references/typescript/gotchas.md - TypeScript-specific mistakes and anti-patterns
references/typescript/error-handling.md - ApplicationFailure, retry policies, non-retryable errors
references/typescript/observability.md - Logging, metrics, tracing
references/typescript/testing.md - TestWorkflowEnvironment, time-skipping, activity mocking
references/typescript/advanced-features.md - Schedules, worker tuning, and more
references/typescript/data-handling.md - Data converters, payload encryption, etc.
references/typescript/versioning.md - Patching API, workflow type versioning, Worker Versioning
references/typescript/standalone-activities.md - Standalone Activities: run an Activity directly from a Client without a Workflow (Public Preview). Concept overview at references/core/standalone-activities.md.
references/typescript/determinism-protection.md - V8 sandbox and bundling

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

2026-11-09

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

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The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download temporal-developer.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Temporal

Skill: temporal-developer

Overview

Core Architecture

History Replay: Why Determinism Matters

Getting Started

Ensure Temporal CLI is installed

Read All Relevant References

Primary References

Task Queue Priority and Fairness

Additional Topics

Third-Party Integrations

Feedback

Reporting Issues in This Skill

Files

references/typescript/typescript.md

Temporal TypeScript SDK Reference

Overview

Understanding Replay

Quick Start

Key Concepts

Workflow Definition

Activity Definition

Worker Setup

File Organization Best Practice

Determinism Rules

Common Pitfalls

Writing Tests

Additional Resources

Reference Files

Requirements and compatibility

Security

Attribution and licence

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MCP Builder

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