Imported from dagucloud/dagu (skills/dagu/SKILL.md). Install upstream with npx skills add dagucloud/dagu --skill dagu. Copyright stays with the author.

DAG Authoring

Load only the reference file that matches the task.

Default Approach

• Prefer type: graph for new DAGs. It supports both sequential flow via depends: and parallel flow.
• Use an Agent DAG (type: agent) only when the step order cannot be written down in advance and an LLM must choose it. It requires llm: and a tasks: list stating when the run is finished. The model may select multiple distinct, independent actions in one turn; Dagu runs them concurrently up to max_active_steps (0 is unlimited, 1 is serial). Same-batch actions cannot consume sibling outputs, while failures do not cancel siblings. set_task_status and ask_user must be called alone.
• Use type: build only for local regular-file pipelines whose unchanged transformations should be reused across runs.
• Prefer id on every step. Omit name unless the display label must differ from the step ID.
• Prefer dagu schema ... and dagu validate ... over guessing field names or shapes.
• Prefer action: template.render when generating text files, prompts, or artifacts instead of assembling them with shell echo or heredocs.
• Prefer file.* actions for local file operations such as stat, read, write, copy, move, delete, mkdir, and list instead of shelling out to cp, mv, rm, or mkdir.
• Prefer git.worktree.add and git.worktree.remove when steps need isolated branches inside an existing local Git repository. Add an explicit remove step when the workflow should delete the worktree.
• Prefer stdout.artifact / stderr.artifact when a command stream should become a DAG-run artifact, especially for large reports, JSON, Markdown, logs, or generated files.
• Prefer artifact.* actions for explicit artifact reads/writes/lists. Use DAG_RUN_ARTIFACTS_DIR only when a tool truly needs a filesystem path inside the step.
• Prefer string-form output: VAR_NAME for capturing small stdout values into flat variables.
• Prefer object-form output: when downstream steps need structured values via ${step_id.output.*}.
• Prefer declared step outputs: with $DAGU_OUTPUT_FILE when a step must publish explicit values for ${steps.<step_id>.outputs.<name>}.
• Use action: human.task when an operator must provide typed input before downstream steps continue. Human task form outputs use ${steps.<step_id>.outputs.<name>} without an authored outputs: field.
• Prefer stdout.outputs or action: outputs.write when a DAG or remote action needs to return caller-visible values via ${step_id.outputs.*}.
• Prefer state.* actions for small persistent JSON state across DAG runs, such as cursors, checkpoints, and previous-value comparisons.
• Prefer temporary files in the artifacts dir only when downstream steps need file paths; otherwise let commands write large artifact content to stdout and attach it with stdout.artifact.
• Prefer scoped Dagu references for named values: ${consts.NAME}, ${params.NAME}, and ${env.NAME}. Avoid unscoped braced names in examples unless the example is intentionally showing shell syntax.
• Declare portable external CLI dependencies in top-level tools using aqua shorthand when the binary version affects reproducibility, for example tools: ["jqlang/jq@jq-1.7.1"]. Append #sha256:<64 hex> to also pin the downloaded artifact content for the run platform, for example jqlang/jq@jq-1.7.1#sha256:<hex>.
• For remote actions, put tools in the referenced action DAG file, not in dagu-action.yaml; caller DAG tools are not inherited across the action boundary.
• Declare step-level dependencies when a run needs files from the DAG working directory. Use literal working-directory-relative paths or glob patterns; do not use value references.
• Use remote action packages (dagu-action.yaml) when reusable logic needs helper files, its own DAG, versioning, or an input/output schema contract.

High-Signal Rules

• output: has two modes:
  • string form captures trimmed stdout into an env-scope variable such as ${env.VERSION}
  • object form publishes structured step-scoped output for ${step_id.output.*} access
• Value declarations in step outputs: publish explicit values through ${steps.<step_id>.outputs.<name>}. Write those values to $DAGU_OUTPUT_FILE; Dagu captures them only after the command succeeds. Build path declarations publish the final materialization path after commit or reuse.
• human.task is a processless root-DAG step with an explicit id, a required with.prompt, and an optional flat scalar form. A root DAG containing one can run locally or on a distributed worker. Every declared form property is a step output, published when submitted or defaulted, and available as ${steps.<step_id>.outputs.<name>}.
• stdout.artifact / stderr.artifact store command stdout/stderr directly as relative artifact paths, for example stdout: {artifact: reports/report.md}. Artifact outputs auto-enable artifacts unless artifacts.enabled: false is explicitly set, which is invalid.
• ${step_id.stdout} is a log file path, not stdout content.
• Use ${context.*} for run metadata in DAG YAML, for example ${context.dag.name}, ${context.run.id}, or ${context.paths.artifacts_dir}. Unavailable context values remain unresolved text instead of becoming empty strings.
• In a build step, ${inputs.<name>} is the final input path and ${outputs.<name>} is a fresh attempt staging path. Write file results only to the staging path; dependencies read the committed path as ${steps.<step_id>.outputs.<name>}.
• Do not read attempt-only ${step_id.stdout}, ${step_id.stderr}, or ${step_id.exit_code} from potentially reusable producers. This also applies to ${step_id.output.<name>} and ${step_id.outputs.<name>}, including their whole-value ${step_id.output} and ${step_id.outputs} forms. Path-output steps cannot use continue_on.mark_success.
• Build workflows are local-only. Path declarations are supported only on host command or shell steps without containers, and stream redirects cannot target declared build inputs or outputs.
• Use ${consts.NAME}, ${params.NAME}, and ${env.NAME} for Dagu-side named values. Use shell $NAME or printenv NAME only when the target shell or process should read the variable at execution time.
• consts: must use list form with one key per item, for example consts: [{service: api}]. Const values are resolved while loading the DAG and can reference inherited or earlier consts.
• env: should use list-of-maps when values depend on earlier env vars.
• params: values arrive as strings. The params: field supports JSON schema-like types and validation, check for schema to see how to specify types and validation rules.
• Single-line run: values are command-form entries. Array-form run: entries run one by one. Multi-line run: values are scripts. Dagu does not split pipes, redirects, &&, or ; into separate commands; those stay with the selected shell.
• Do not assume bash for run: steps. If a script depends on a specific interpreter, add a shebang such as #!/bin/sh or #!/usr/bin/env bash only after checking that shell exists on the target host or container. Otherwise keep the script portable or set with.shell: explicitly.
• parallel: currently requires action: dag.run to a child DAG.
• Sub-DAGs do not inherit parent env vars; pass what you need via params:.
• For arbitrary text inside shell steps, prefer printenv VAR_NAME or action: template.render over Dagu interpolation such as ${env.VAR_NAME}.
• harness.run supports built-in provider adapters (aider, amp, claude, cline, codex, copilot, cursor, deepseek, droid, gemini, goose, kiro, opencode, pi, qwen) and custom top-level harnesses: entries. Built-in OpenCode uses managed sessions on long-lived Dagu hosts by default; containers and unsupported options use the CLI path. It can use top-level container: or step-level container:.
• Container runtime selection is service-level, not a DAG YAML field. Set DAGU_CONTAINER_RUNTIME=podman to use Podman, and set DAGU_PODMAN_HOST only when the Podman Docker-compatible socket is not the default.
• DAG/action outputs are collected from string-form output: VAR_NAME, stdout.outputs, and action: outputs.write. Object-form output: stays step-scoped for ${step_id.output.*} unless the workflow explicitly republishes values through stdout.outputs or outputs.write.
• state.get, state.set, state.delete, state.list, and state.diff persist small JSON values across DAG runs. State scopes are dag, root_dag, global, and custom; use artifacts or external storage for large payloads.
• Git worktree actions discover the repository from the step working_dir. Relative worktree paths resolve from the repository root, and the actions never fetch or push.
• Remote action packages define dagu-action.yaml with apiVersion: v1alpha1, name, dag, and optional inputs/outputs JSON Schemas. inputs validates caller with: before the action DAG starts; outputs validates the final action output object after the action DAG returns.
• Remote action manifests do not support tools. Declare external CLI tools in the action DAG itself so local and distributed workers prepare the right binaries for that action run.
• dependencies snapshots files from the DAG working directory for both local and distributed execution. The materialized bundle is available through DAG_RUN_WORK_DIR and ${context.paths.work_dir} and becomes the DAG process working directory.
• In remote action examples, prefer dag: workflow.yaml for the action DAG filename. The dag field accepts any safe relative file path, but workflow.yaml avoids confusing the executable DAG with the dagu-action.yaml manifest.
• Object-form output: with decode: json or decode: yaml can act as lightweight runtime validation. Malformed data or an unresolved select: path fails the step, so normal retry_policy applies.
• Use DAG-level shell and shell_args only when every inherited run: step should use the same shell invocation. Use step-level with.shell and with.shell_args for a single step.
• Use dagu schema dag to check the full list of available fields and their shapes.
• Use dagu example to see different DAG patterns and how to express them in YAML.

Example of Params, template step, and artifacts

params:
  type: object
  properties:
    name:
      type: string
      maxLength: 50
    age:
      type: integer
      minimum: 0
      maximum: 120
    favorite_color:
      type: string
  required: [name, age]

steps:
  - id: render
    action: template.render
    with:
      data:
        name: ${params.name}
        age: ${params.age}
        favorite_color: ${params.favorite_color}
      template: |
        Hello, {{ .name }}!
        You are {{ .age }} years old.
        {{- if .favorite_color }}
        Your favorite color is {{ .favorite_color }}.
        {{- end }}
    stdout:
      artifact: greeting.txt

Example of Large Command Output as Artifact

steps:
  - id: report
    run: ./generate-report --format markdown
    stdout:
      artifact: reports/report.md

Example of Reproducible External CLI

tools:
  - jqlang/jq@jq-1.7.1

steps:
  - id: inspect
    run: jq --version

Example of Object-Form Output

steps:
  - id: inspect_build
    run: echo '{"version":"v1.2.3","artifact":{"url":"https://example.test/app.tgz"}}'
    output:
      # decode + select act as a lightweight contract check:
      # malformed JSON or a missing selected field fails the step.
      version:
        from: stdout
        decode: json
        select: .version
      artifact:
        from: stdout
        decode: json
        select: .artifact

  - id: publish
    depends: [inspect_build]
    output:
      versionLabel: "ver - ${inspect_build.output.version}"
      artifactUrl: "${inspect_build.output.artifact.url}"

Example of Action Outputs

steps:
  - id: classify
    run: ./classify.sh "${params.INPUT}"
    stdout:
      outputs:
        fields:
          label:
            decode: json
            select: .label
          confidence:
            decode: json
            select: .confidence

  - id: publish
    depends: [classify]
    action: outputs.write
    with:
      values:
        label: ${classify.outputs.label}
        reviewed: false

Example of Human Input

steps:
  - id: review
    action: human.task
    with:
      prompt: Choose the deployment target
      form:
        type: object
        properties:
          environment:
            type: string
            enum: [staging, production]
          note:
            type: string
            default: ""
        required: [environment]

  - id: deploy
    depends: [review]
    run: ./deploy --environment '${steps.review.outputs.environment}' --note '${steps.review.outputs.note}'

Complete the task from a local CLI context with dagu human-task complete --run-id=<run-id> --step=review --input environment=production <dag-name>. A form is optional for acknowledgement-only tasks. Human tasks cannot be used in sub-DAGs; a distributed root run is re-queued through the scheduler after completion.

Reference Guide

Load only the file you need:

• references/steptypes.md when choosing an action or checking action-specific behavior such as human.task, dag.run, parallel, git.worktree.*, jq.filter, file.*, state.*, or template.render
• references/dagu-action.md when creating a reusable dagu-action.yaml package or checking action input/output schema behavior
• references/cli.md when choosing or using Dagu CLI commands, including workflow inspection, execution, and cleanup operations
• references/context.md when using ${context.*} metadata references or declared step outputs:
• references/build.md when creating or troubleshooting a type: build file workflow, path references, reuse decisions, or --no-reuse
• references/file-dependencies.md when a DAG needs scripts, configuration, or other files from its working directory
• references/harnesses.md only when the DAG invokes external CLI harnesses through harness.run