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Dbos Python

Checked
dbos-inc·vlatest·backend·MIT

Automates database interactions and data processing tasks using Python scripts within your dbOS environment.

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 dbos-inc/agent-skills --skill dbos-python -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

dbos-inc

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 dbos-inc/agent-skills at 46ebebbb35.

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

Commit
46ebebbb35
Manifest
skills/dbos-python/SKILL.md
Scanned
40 files, 3,576 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 automate database interactions and data processing tasks using Python scripts within a dbOS environment. It provides guidelines for building reliable, fault-tolerant Python applications utilizing DBOS durable workflows, including configuring and launching applications, managing concurrency with queues, and implementing communication between workflows. The skill focuses on best practices for integrating DBOS into existing Python codebases.

When to use it

  • Adding DBOS functionality to existing Python code.
  • Creating new workflows and individual steps within a dbOS application.
  • Implementing concurrent task processing using queues.
  • Configuring and launching DBOS applications.
  • Testing the behavior of DBOS applications.

Key capabilities

  • Defining workflows composed of deterministic steps.
  • Using @DBOS.workflow to designate workflow functions.
  • Utilizing @DBOS.step to mark functions performing complex operations or accessing external services.
  • Configuring and launching DBOS applications with a DBOSConfig.
  • Managing concurrency using queues.
  • Implementing communication between workflows via events, messages, and streams.

Example prompts

  • "Create a dbOS workflow that calls an external API."
  • "How do I configure my Python application to launch within DBOS?"
  • "Show me an example of using a queue for concurrency control in dbOS."

Tips & gotchas

  • Workflows must be deterministic; non-deterministic operations should be placed within steps.
  • Avoid calling DBOS.start_workflow or DBOS.recv from within a step.
  • Refer to the detailed rule files (e.g., references/lifecycle-config.md, references/workflow-determinism.md) for comprehensive explanations and examples.