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Dbos Python

Listed
sickn33·vlatest·backend·MIT

Automates Python backend tasks like data processing, API integration, and scripting using sickn33's specialized libraries.

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 sickn33/agentic-awesome-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

sickn33

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/dbos-python/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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

The sickn33-dbos-python skill provides Python integration with Distributed Backup Object Storage (DBOS). It allows AI agents to interact with DBOS using standard Python libraries, enabling them to read and write data stored in a distributed object store. This facilitates persistent storage and retrieval of information for the agent's long-term memory and state management.

When to use it

  • Persistent Agent State: Store and retrieve complex agent states across sessions or restarts.
  • Long-Term Memory: Implement a durable knowledge base by storing documents, embeddings, or other data in DBOS.
  • Data Backup & Recovery: Automatically back up critical agent data to ensure resilience against failures.
  • Sharing Data Across Agents: Enable multiple agents to access and share information stored within the DBOS environment.

Key capabilities

  • Python integration with DBOS
  • Read/Write operations for objects in DBOS
  • Uses standard Python libraries

Example prompts

  • "Save this document to DBOS under the key 'agent_notes/meeting_summary'."
  • "Retrieve the data stored at the DBOS path 'agent_state/last_known_location'."
  • "Backup my current working memory to DBOS with a timestamped filename."

Tips & gotchas

Requires a configured DBOS environment and appropriate credentials for the AI agent. Familiarity with Python is necessary to effectively utilize this skill's capabilities.