Update Sparkflows workflows by applying deterministic node and edge changes.
npx skills add https://github.com/sparkflows/vscode --skill workflow-update-sparkflows
Please help me install this Agent Skill. Skill: workflow-update Source: https://github.com/sparkflows/vscode/tree/main/workflow-update Command: npx skills add https://github.com/sparkflows/vscode --skill workflow-update-sparkflows
Updates an existing Sparkflows workflow by applying user-specified changes to its nodes and edges, enabling rapid evolution of data pipelines without recreating workflows from scratch.
Update an existing Sparkflows workflow by describing precise changes to apply (e.g., "update workflow 1234 to add a filter after node 2" or "rename node 5 input path to s3://...").
High-intent search queries and answers about installing and using this skill.
To update an existing Sparkflows workflow, provide the workflow ID and describe the precise changes to apply to its nodes and edges. The update executes in a deterministic sequence to preserve graph integrity without requiring a full recreation.
The safest order for modifying nodes and edges is deterministic: remove edges, remove nodes, add nodes, add edges, and finally update parameters. This specific sequence prevents broken connections and preserves graph integrity during pipeline updates.
Yes, you can reconfigure node parameters and reroute connections by specifying the target workflow ID and the desired changes. The update process applies these modifications safely to adapt your data pipelines dynamically.
To modify a Sparkflows workflow using automation, you need the specific workflow ID to fetch the existing pipeline. You also need the requests library installed to handle the API interactions for re-importing the updated workflow.
Workflow updates may fail if nodes are added before edges are properly removed or rerouted. The system enforces a strict deterministic update order to prevent such conflicts, ensuring edges are removed before any structural additions occur.
Yes, the script works with the Sparkflows server by using the workflow ID to fetch, modify, and re-import the updated workflow. This integration enables rapid evolution of data pipelines directly within the server environment.
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