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Skills temporal-python-pro
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temporal-python-pro
Content revision r2 Safe ⚙️ External commands
Build Reliable Temporal Workflows in Python
Distributed workflows are difficult to make deterministic, retryable, and observable. This skill provides focused Python SDK guidance for design, testing, and production operations.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "temporal-python-pro" from https://skillstore.io/skills/sickn33-temporal-python-pro.md and its manifest at https://skillstore.io/api/skills/sickn33-temporal-python-pro/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "temporal-python-pro". Design retry behavior for a payment activity.
Expected outcome:
- Classify network failures as retryable and validation failures as permanent.
- Set a bounded exponential backoff policy and a total activity timeout.
- Use an idempotency key so retries cannot create duplicate charges.
- Add compensation behavior when later order steps fail.
Using "temporal-python-pro". Create a testing checklist for a month-long approval workflow.
Expected outcome:
- Use time skipping to exercise every deadline without waiting.
- Mock approval activities and inject transient and permanent failures.
- Test duplicate and late signals for idempotent behavior.
- Replay representative histories before releasing workflow changes.
Using "temporal-python-pro". Review production worker readiness.
Expected outcome:
The review covers task queue alignment, registered workflows, concurrency limits, graceful shutdown, health metrics, tracing, and compatible rollout procedures.
Security Audit
Safev5 • 9/6/2026 Open versioned report
All 20 command-execution alerts are false positives caused by Markdown code spans that name Python and Temporal APIs. The reconnaissance alert describes read-only workflow queries, and no semantic security threats were found.
1
Files scanned
380
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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APA citation
sickn33. (2026). temporal-python-pro security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-temporal-python-pro/audits/5BibTeX citation
@techreport{sickn33-sickn33-temporal-python-pro-2026,
author = {sickn33},
title = {temporal-python-pro security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-temporal-python-pro/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "temporal-python-pro security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-09-06"
url: "https://skillstore.io/skills/sickn33-temporal-python-pro/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-temporal-python-pro:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance
What You Can Build
Create a Durable Order Workflow
Design an order process with retryable activities, timeouts, and compensation for failed payments or inventory reservations.
Test Long-Running Business Processes
Plan time-skipping tests, activity mocks, error injection, and replay checks for workflows lasting days or months.
Prepare Workers for Production
Review worker scaling, task queues, graceful shutdown, observability, and version rollout for a production deployment.
Try These Prompts
Explain a Temporal Concept
Explain the difference between a Temporal workflow and an activity in Python. Include determinism, retries, and one practical example.
Design a Workflow
Design a Temporal Python workflow for [process]. Define inputs, activities, timeouts, retries, signals, queries, and failure behavior.
Review an Implementation
Review my Temporal Python workflow for determinism, idempotency, blocking calls, timeout coverage, retry safety, and payload limits. Explain each finding.
Plan Production Evolution
Create a production migration plan for changing [workflow]. Cover replay compatibility, worker versioning, rollout, rollback, monitoring, and validation.
Best Practices
- Keep workflow logic deterministic and move external calls into activities.
- Make activities idempotent and define explicit retry, timeout, heartbeat, and cancellation behavior.
- Test failures, compensation, time progression, and replay compatibility before deployment.
Avoid
- Do not call external services or use nondeterministic system APIs directly inside workflows.
- Do not run blocking libraries in async activities because they can stall the event loop.
- Do not deploy workflow changes without replay testing and a compatible versioning strategy.
Frequently Asked Questions
What does this skill help build?
It helps design Temporal workflows, activities, workers, tests, and production operating practices with the Python SDK.
Does it connect to a Temporal cluster?
No. It provides guidance and examples but does not connect to or modify a cluster.
Can it review existing workflow code?
Yes. Provide the relevant code and requirements for a review of determinism, retries, timeouts, idempotency, and deployment risks.
Does it cover workflow testing?
Yes. It covers time skipping, mocked activities, error injection, integration tests, and replay validation.
Can it help with saga patterns?
Yes. It can plan ordered activities, failure handling, and compensation steps for distributed transactions.
What information improves the result?
Provide the business process, failure rules, task queues, expected duration, payloads, dependencies, and deployment constraints.
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/temporal-python-proRef
ae6ba0f1a47f0b4427a656b2202f2ff34bfea6be
Maintenance freshness
9/6/2026
Usage
9 downloads · 128 views
File structure
📄 SKILL.md
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