Skip to content
TrustedSkillsbeta
Back to all skills

Temporal Python Pro

Checked
rmyndharis·vlatest·backend·MIT

Analyzes historical Python codebases to predict future maintenance needs and suggest proactive refactoring strategies.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add rmyndharis/antigravity-skills --skill temporal-python-pro -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

rmyndharis

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned rmyndharis/antigravity-skills at 3eff4af253.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3eff4af253
Manifest
skills/temporal-python-pro/SKILL.md
Scanned
1 file, 370 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to leverage Temporal Python for robust, fault-tolerant workflow orchestration. It allows the agent to define and execute complex tasks as distributed workflows, automatically handling retries, state management, and ensuring reliable completion even in the face of failures. The skill provides a framework for building long-running processes that require coordination across multiple services or components.

When to use it

  • Automating data pipelines: Schedule and manage ETL (Extract, Transform, Load) jobs with automatic error recovery.
  • Orchestrating complex business processes: Implement multi-step approval workflows or order processing systems requiring reliable execution.
  • Building asynchronous task queues: Offload long-running tasks from a main application thread to improve responsiveness and scalability.
  • Managing distributed microservices interactions: Coordinate actions across multiple microservices, ensuring consistency and resilience.

Key capabilities

  • Temporal Python integration
  • Workflow definition using Python code
  • Automatic retry mechanisms for task failures
  • State management within workflows
  • Distributed execution of tasks

Example prompts

  • "Create a Temporal workflow to process customer orders, including inventory checks and payment authorization."
  • "Define a Temporal activity that fetches data from an external API and transforms it into a specific format."
  • “Run the ‘data_ingestion’ temporal workflow with these parameters: source=s3://mybucket/data.csv, destination=postgres://user:pass@host:port/db”

Tips & gotchas

  • Requires Temporal Python to be installed and configured in the environment where the agent is running.
  • Workflow definitions should be carefully designed to handle potential errors and edge cases for reliable operation.