A guide for using the DBOS Python SDK, which helps Python applications continue reliably through failures. It covers durable workflows, steps, queues, communication, clients, and testing.

Creating and testing DBOS workflows, controlling concurrent work with queues, sending messages or events, launching applications, and connecting external programs through DBOSClient.

It gives coding agents rules for adding DBOS correctly, reducing mistakes when building applications that must recover from failures.

dbos-python — Skill by dbos-inc

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

Any agent

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

Clone the repo

git clone --depth 1 https://github.com/dbos-inc/agent-skills

Made for: Claude Code, Codex.

Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 778 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. Scan, not verified.

Origin original No closer match found 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.

Model	Per session	Once invoked
Fable 5	$0.00059	$0.00778
Opus 5	$0.00030	$0.00389
Sonnet 5	$0.00012	$0.00156
Haiku 4.5	$0.00006	$0.00078

Measured 2d ago against content hash 57678fb88b99, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dbos-python scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

return requests.get("https://api.example.com").json()

skills/dbos-python/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DBOS Python Best Practices

Guide for building reliable, fault-tolerant Python applications with DBOS durable workflows.

When to Apply

Reference these guidelines when:

Adding DBOS to existing Python code
Creating workflows and steps
Using queues for concurrency control
Implementing workflow communication (events, messages, streams)
Configuring and launching DBOS applications
Using DBOSClient from external applications
Testing DBOS applications

Rule Categories by Priority

Priority	Category	Impact	Prefix
1	Lifecycle	CRITICAL	`lifecycle-`
2	Workflow	CRITICAL	`workflow-`
3	Step	HIGH	`step-`
4	Queue	HIGH	`queue-`
5	Communication	MEDIUM	`comm-`
6	Pattern	MEDIUM	`pattern-`
7	Testing	LOW-MEDIUM	`test-`
8	Client	MEDIUM	`client-`
9	Advanced	LOW	`advanced-`

Critical Rules

DBOS Configuration and Launch

A DBOS application MUST configure and launch DBOS inside its main function:

import os
from dbos import DBOS, DBOSConfig

@DBOS.workflow()
def my_workflow():
    pass

if __name__ == "__main__":
    config: DBOSConfig = {
        "name": "my-app",
        "application_version": "0.1.0",
        "system_database_url": os.environ.get("DBOS_SYSTEM_DATABASE_URL"),
    }
    DBOS(config=config)
    DBOS.launch()

When creating a new application, set application_version to "0.1.0". If omitted, DBOS derives an opaque hash from workflow source code. When editing an existing application, leave its configured version alone — changing it is a deployment decision (see references/advanced-versioning.md).

Workflow and Step Structure

Workflows are comprised of steps. Any function performing complex operations or accessing external services must be a step:

@DBOS.step()
def call_external_api():
    return requests.get("https://api.example.com").json()

@DBOS.workflow()
def my_workflow():
    result = call_external_api()
    return result

Read the full file on GitHub · 104 lines

Files

What ships with it

38 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

2d ago First seen · 104 lines · 59 tokens per session scan A 57678fb88b99

Subscribe to this mod's changes

dbos-python is a skill published in the GitHub repository dbos-inc/agent-skills (17 stars, last pushed 11d ago), licensed MIT. It adds 59 tokens to every session and 778 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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dbos-python