Create Dataflow
npx machina-cli add skill PabloLION/bmad-plugin/create-dataflow --openclawCreate Dataflow Diagram
Goal: Create data flow Excalidraw diagram.
Agent: Tech Writer (Paige) Phase: Diagrams
Execution
Read and follow: ./instructions.md
Validation
After completion, verify against: ./checklist.md
Source
git clone https://github.com/PabloLION/bmad-plugin/blob/main/plugins/bmad/skills/create-dataflow/SKILL.mdView on GitHub Overview
Create Dataflow Diagram helps you visually map data movement across systems using Excalidraw. It produces a clear, shareable diagram that highlights data sources, transformations, storage, and destinations. The process starts by reading ./instructions.md and ends with validation against ./checklist.md to ensure completeness.
How This Skill Works
The workflow begins by referencing ./instructions.md to guide diagram requirements, then you build the data flow diagram in Excalidraw following those guidelines. Upon completion, you validate the diagram against ./checklist.md to ensure all criteria are met.
When to Use It
- Document a new data pipeline in your project
- Map data flow during system redesign or integration
- Explain data sources and sinks to stakeholders
- Create a reproducible data-flow reference for audits
- Share a lightweight diagram for onboarding new team members
Quick Start
- Step 1: Open a new Excalidraw canvas for the diagram.
- Step 2: Read ./instructions.md to understand requirements and constraints.
- Step 3: Build the diagram and then validate against ./checklist.md.
Best Practices
- Start with high-level data sources and sinks before detailing transformations
- Label all data flows with clear names and units where applicable
- Keep arrow directions consistent and avoid crossing lines when possible
- Follow instructions.md for diagram requirements and use the checklist.md for validation
- Save or export the diagram from Excalidraw and share the file with stakeholders
Example Use Cases
- Map user data flow from frontend to backend services and database
- Illustrate an ETL pipeline from raw data lake to curated tables
- Show API data exchange between microservices and third-party integrators
- Document a data backup and disaster recovery data path
- Visualize analytics data movement from ingestion to dashboards