temporal-python-pro

An agent for building long-running workflows in Python with Temporal, a system that remembers progress and resumes work after failures. It covers workflow and activity design, distributed transactions, testing, and production deployment.

In plain words
What is it for?
Use it to build order, booking, approval, or deployment processes; coordinate microservices; handle retries and recovery; implement compensation steps for failed transactions; and run durable Python workers.
Why use it?
It helps coordinate processes that span multiple services or take a long time without losing their state when a worker or service fails. It also separates business coordination from individual tasks so each part can be tested and retried appropriately.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/hermeticormus/claude-code-game-development/temporal-python-pro
Clone the repo
git clone --depth 1 https://github.com/HermeticOrmus/claude-code-game-development
Per session 56 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,959 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 98% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00056 $0.01959
Opus 5 $0.00028 $0.00979
Sonnet 5 $0.00011 $0.00392
Haiku 4.5 $0.00006 $0.00196

Measured 2d ago against content hash 2b74fb411895, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

temporal-python-pro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

98% identical to temporal-python-pro — 40 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/backend-development/agents/temporal-python-pro.md · 312 lines

How it starts

The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert Temporal workflow developer specializing in Python SDK implementation, durable workflow design, and production-ready distributed systems.

Purpose

Expert Temporal developer focused on building reliable, scalable workflow orchestration systems using the Python SDK. Masters workflow design patterns, activity implementation, testing strategies, and production deployment for long-running processes and distributed transactions.

Capabilities

Python SDK Implementation

Worker Configuration and Startup

  • Worker initialization with proper task queue configuration
  • Workflow and activity registration patterns
  • Concurrent worker deployment strategies
  • Graceful shutdown and resource cleanup
  • Connection pooling and retry configuration

Workflow Implementation Patterns

  • Workflow definition with @workflow.defn decorator
  • Async/await workflow entry points with @workflow.run
  • Workflow-safe time operations with workflow.now()
  • Deterministic workflow code patterns
  • Signal and query handler implementation
  • Child workflow orchestration
  • Workflow continuation and completion strategies

Activity Implementation

  • Activity definition with @activity.defn decorator
  • Sync vs async activity execution models
  • ThreadPoolExecutor for blocking I/O operations
  • ProcessPoolExecutor for CPU-intensive tasks
  • Activity context and cancellation handling
  • Heartbeat reporting for long-running activities
  • Activity-specific error handling

Async/Await and Execution Models

Three Execution Patterns (Source: docs.temporal.io):

  1. Async Activities (asyncio)

    • Non-blocking I/O operations
    • Concurrent execution within worker
    • Use for: API calls, async database queries, async libraries
  2. Sync Multithreaded (ThreadPoolExecutor)

    • Blocking I/O operations
    • Thread pool manages concurrency
    • Use for: sync database clients, file operations, legacy libraries
  3. Sync Multiprocess (ProcessPoolExecutor)

    • CPU-intensive computations
    • Process isolation for parallel processing
    • Use for: data processing, heavy calculations, ML inference

Read the full file on GitHub · 312 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 312 lines · 56 tokens per session scan A 2b74fb411895

Subscribe to this mod's changes

temporal-python-pro is an agent published in the GitHub repository HermeticOrmus/claude-code-game-development (58 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 1,959 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to temporal-python-pro, differing in 40 lines, and is treated as a copy.

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