Author a Workflow

Use an AI agent to author and submit a new Argo Workflow.

Drafting a new Argo Workflow from scratch is one of the higher-friction tasks in Argo. The YAML is verbose, template references are easy to mis-type, and parameter/artifact passing has its own conventions. An AI agent connected to the Pipekit MCP server can short-circuit a lot of that because the server ships authoring guidance as resources.

How the agent authors and submits a Workflow

Given a goal (e.g. "build a DAG that fans out over a list and aggregates"), the agent:

1. Reads pipekit://guides/workflow-authoring for Pipekit-specific submission rules and limits.

2. Reads pipekit://guides/parameters-and-artifacts and pipekit://guides/template-types to pick the right template type and parameter passing strategy.

3. Reads pipekit://guides/offline-lint-templateref-footgun if the workflow references shared WorkflowTemplates (this guide covers the most common authoring mistake: referencing a Template that won't resolve when the workflow runs).

4. Drafts the workflow YAML.

5. Optionally calls list_clusters to confirm the target cluster name.

6. Calls submit_workflow to submit.

Example: S3 fanout DAG to Slack

I want a Workflow that:
- Pulls a list of files from S3
- Fans out, one task per file
- Aggregates the per-file outputs into a single summary
- Posts the summary to Slack

Submit it to cluster `data-dev`, namespace `argo`, service account `argo-workflow`.

The agent drafts a Workflow with a DAG template, an artifact-based fanout, and a final aggregation step. It calls submit_workflow once it has a complete spec. You'll be prompted to confirm submit_workflow if your client honors MCP annotations (it's additive, not destructive, but most clients still prompt on any state change).

Argo Workflow authoring best practices

• Always set namespace and serviceAccountName. The agent will ask if you don't specify them. If you can't be bothered, paste your team's defaults into the prompt. The agent will reuse them.

• Specify generateName, not name. This is the convention that lets Pipe group Runs together. The authoring guide makes the same point.

• Validate locally if you can. Argo's argo lint will catch most YAML problems before submission. If your team has a local validation step, mention it in the prompt and the agent will run it before calling submit_workflow.

Permission notes

submit_workflow is annotated destructiveHint: false (additive: creates a new Run, never overwrites). MCP-annotation-aware clients may still prompt before any tool that changes state. For the full list, see Tool Inventory.