Standard Inputs
Orders, inventory, and support tickets are represented as CSV inputs with explicit fields.
A simulated-data portfolio project that turns weekly ecommerce operations review into one reusable AI Skill, Python CLIs, CSV inputs, a Markdown risk report, evidence validation, and human-review boundaries.
The project demonstrates a transferable operating pattern: standardize repeated work, generate draft analysis, and keep business decisions under human review.
Orders, inventory, and support tickets are represented as CSV inputs with explicit fields.
The CLI generates a Markdown weekly report with summary metrics, SKU risk levels, and action tags.
Inventory, refund, customer-promise, and owner-assignment decisions remain human-reviewed.
A second CLI checks that evidence-matrix file references exist and that safe wording boundaries remain present.
The workflow mirrors a real weekly operations review, but uses only simulated data in this public demo.
Normalize order, inventory, and ticket inputs.
Flag low stock, refunds, late shipments, and unresolved negative tickets.
Generate a Markdown weekly report and action queue.
Human owners confirm actions before real use.
This ecommerce demo is included as operating-method evidence: repeated work can be converted into structured inputs, reusable AI instructions, generated reports, tests, and review checkpoints.
Reviewers can inspect the repo, release, test workflow, sample data, generated report, and evidence matrix directly.