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Developer Workflow · Public

dagu

Developer workflow project for checking task state, code/agent collaboration, permissions, and delivery boundaries.

Developer workflowTask boardAgent collaborationState managementDelivery boundaries

Last verification date: 2026-07-26 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Publication status · 2026-07-26

What is dagu?

01

Quick decision

Use this section to decide whether the project is worth a deeper read.
Best forDevelopers organizing code tasks, agent collaboration, or engineering state into a reviewable workflow.

Match the project to your task before installing it.

CapabilityTask-state checks, agent collaboration boundaries, permission paths, delivery acceptance, and rollback guidance

Developer workflow project for checking task state, code/agent collaboration, permissions, and delivery boundaries.

Repositorydagucloud/dagu

3.7k stars · 297 forks

02

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.
1

Overview

Related topics: Lib

Source: https://github.com/dagucloud/dagu / Human Manual
2

Lib

Related topics: Overview, Lib

Source: https://github.com/dagucloud/dagu / Human Manual
3

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records
4

Community Discussion Evidence

These external discussion links are review inputs, not standalone proof that the project is production-ready.

Source: Project Pack community evidence and pitfall evidence

Sources: https://github.com/dagucloud/dagu, Human Manual, Project Pack evidence, and downstream validation signals.

03

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.
Stars3.7k stars
Forks297 forks
Contributors83 contributors
Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using dagu with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

04

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.
1

Try the prompt first

Test the workflow without installing the upstream project.

preview
2

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual
3

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context
4

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify
docker run --rm -v ~/.dagu:/var/lib/dagu -p 8080:8080 ghcr.io/dagucloud/dagu:latest dagu start-all

Official start command · https://github.com/dagucloud/dagu#readme · verified: yes

05

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

dagu Manual

Local-first workflow engine for ops automation and AI-assisted operations. Open source and self-hostable: single binary, no DBMS. Define DAGs in declarative YAML. Built-in MCP server so AI agents can manage your DAGs.

Open the full manual
  1. https://github.com/dagucloud/dagu Project Manual
  2. Table of Contents
  3. Overview
  4. Related Pages
  5. Core Components and Runtime Layout
  6. Deployment Options
  7. Key Features
  8. Operational Notes and Known Gaps
1

Overview

Related topics: Lib

Source: https://github.com/dagucloud/dagu / Human Manual
2

Lib

Related topics: Overview, Lib

Source: https://github.com/dagucloud/dagu / Human Manual
3

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records
4

Community Discussion Evidence

These external discussion links are review inputs, not standalone proof that the project is production-ready.

Source: Project Pack community evidence and pitfall evidence

06

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

07

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

08

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.
high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

Developers may fail before the first successful local run: bug: `stdout.outputs` declared on a `handler_on` step is captured but never published to the DAG run outputs

medium

Installation risk requires verification

Developers may fail before the first successful local run: bug: queued run that fails before startup is never dequeued and retries forever

medium

Installation risk requires verification

Upgrade or migration may change expected behavior: helm-dagu-1.0.10

medium

Installation risk requires verification

Upgrade or migration may change expected behavior: helm-dagu-1.0.11

medium

Installation risk requires verification

Developers may fail before the first successful local run: question: `onInit` handler is recorded but never displayed — is that intended?

medium

Installation risk requires verification

Upgrade or migration may change expected behavior: v2.10.0