Agent Academy

Agent Academy is a free, source-linked library of skills, prompts, MCP servers and bot templates, organised into courses by profession, for people who hand real work to AI agents: 1,467 live resources, each with its original link, license and safety tags.

Skill

workflow-orchestration-patterns

Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

No credentialsDoes not send

https://github.com/wshobson/agents/blob/main/plugins/backend-development/skills/workflow-orchestration-patterns/SKILL.md

Install
npx skills add wshobson/agents --skill workflow-orchestration-patterns

Original content

Full originalMITSource

Republished in full under its license, with attribution. The source is authoritative.

name: workflow-orchestration-patterns
description: Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

Workflow Orchestration Patterns

Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems.

When to Use Workflow Orchestration

Ideal Use Cases (Source: docs.temporal.io)

  • Multi-step processes spanning machines/services/databases
  • Distributed transactions requiring all-or-nothing semantics
  • Long-running workflows (hours to years) with automatic state persistence
  • Failure recovery that must resume from last successful step
  • Business processes: bookings, orders, campaigns, approvals
  • Entity lifecycle management: inventory tracking, account management, cart workflows
  • Infrastructure automation: CI/CD pipelines, provisioning, deployments
  • Human-in-the-loop systems requiring timeouts and escalations

When NOT to Use

  • Simple CRUD operations (use direct API calls)
  • Pure data processing pipelines (use Airflow, batch processing)
  • Stateless request/response (use standard APIs)
  • Real-time streaming (use Kafka, event processors)

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices

Workflow Design

  1. Keep workflows focused - Single responsibility per workflow
  2. Small workflows - Use child workflows for scalability
  3. Clear boundaries - Workflow orchestrates, activities execute
  4. Test locally - Use time-skipping test environment

Activity Design

  1. Idempotent operations - Safe to retry
  2. Short-lived - Seconds to minutes, not hours
  3. Timeout configuration - Always set timeouts
  4. Heartbeat for long tasks - Report progress
  5. Error handling - Distinguish retryable vs non-retryable

Common Pitfalls

Workflow Violations:

  • Using datetime.now() instead of workflow.now()
  • Threading or async operations in workflow code
  • Calling external APIs directly from workflow
  • Non-deterministic logic in workflows

Activity Mistakes:

  • Non-idempotent operations (can't handle retries)
  • Missing timeouts (activities run forever)
  • No error classification (retry validation errors)
  • Ignoring payload limits (2MB per argument)

Operational Considerations

Monitoring:

  • Workflow execution duration
  • Activity failure rates
  • Retry attempts and backoff
  • Pending workflow counts

Scalability:

  • Horizontal scaling with workers
  • Task queue partitioning
  • Child workflow decomposition
  • Activity batching when appropriate

Additional Resources

Official Documentation:

  • Temporal Core Concepts: docs.temporal.io/workflows
  • Workflow Patterns: docs.temporal.io/evaluate/use-cases-design-patterns
  • Best Practices: docs.temporal.io/develop/best-practices
  • Saga Pattern: temporal.io/blog/saga-pattern-made-easy

Key Principles:

  1. Workflows = orchestration, Activities = external calls
  2. Determinism is non-negotiable for workflows
  3. Idempotency is critical for activities
  4. State preservation is automatic
  5. Design for failure and recovery

Related

SkillSoftware engineering

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`,…

Sourcegithub.com/anthropics/skills/blob/main/skills/claude-api/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

doc-coauthoring

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar…

Sourcegithub.com/anthropics/skills/blob/main/skills/doc-coauthoring/SKILL.md

No credentialsDoes not sendnot stated
SkillSoftware engineering

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Sourcegithub.com/anthropics/skills/blob/main/skills/mcp-builder/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

skill-creator

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Sourcegithub.com/anthropics/skills/blob/main/skills/skill-creator/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

webapp-testing

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

Sourcegithub.com/anthropics/skills/blob/main/skills/webapp-testing/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

ai-debt-detector

Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.

Sourcegithub.com/wshobson/agents/blob/main/plugins/skill-forge-essentials/skills/ai-debt-detector/SKILL.md

No credentialsDoes not sendMIT