merch-report-html

# Merch Report (interactive HTML) This skill produces the **shareable report** that closes out the end-of-quarter markdown review by **running the bundled `merch_report.py` script**. You do **not** write any Python and you do **not** invent numbers: every value comes from the earlier steps. The script renders one **self-contained, interactive HTML file** (BlastBox Omega theme) - all CSS, JavaScript, and SVG charts are inlined, so it references nothing external and works fully offline once downloaded. Use this as the **last** step, after `sales-analysis` has produced the top sellers and slow movers and `markdown-optimizer` has produced the policy-bound recommendations. ## Inputs (pass the JSON you already have as flags) | Flag | Source | | --- | --- | | `--top-sellers` | top sellers from `sales-analysis` - `[{name, units, velocity, revenue}]` | | `--slow-movers` | slow movers from `sales-analysis` - `[{name, sku, weeks_of_cover, price, cost, margin}]` | | `--recommendations` | `RECOMMENDATIONS_JSON` from `markdown-optimizer` - `[{name, sku, price, rec_discount_pct, new_price, new_margin, binding, flag_clearance}]` | | `--policy` | the guardrails from the Store Policy Agent - `{max_discount_pct, margin_floor_pct, min_useful_promo_discount_pct}` | | `--window` | the review window label, e.g. `"Apr 12 - May 31, 2026"` | | `--weeks` | analysis window length (default 8) | | `--woc-threshold` | slow-mover weeks-of-cover threshold (default 8) | | `--out` | output path (default `merch_report.html`) | ## Run the bundled script ```bash python3 merch_report.py \ --window "Apr 12 - May 31, 2026" --weeks 8 \ --top-sellers '[{"name":"MEGA Lizards from Outer Space","units":540,"velocity":67.5,"revenue":37794.6}]' \ --slow-movers '[{"name":"OmegaVision VR Headset","sku":"SKU-VR-GOGGLES","weeks_of_cover":64.0,"price":199.99,"cost":70.0,"margin":65.0}]' \ --recommendations '[{"name":"OmegaVision VR Headset","sku":"SKU-VR-GOGGLES","price":199.99,"rec_discount_pct":30.0,"new_price":139.99,"new_margin":50.0,"binding":"max_discount","flag_clearance":false}]' \ --policy '{"max_discount_pct":30,"margin_floor_pct":15,"min_useful_promo_discount_pct":10}' ``` The script writes `merch_report.html` to the working directory and prints a one-line confirmation (file size + counts). Hand that file back as a **download**. ## What the report contains (so you can describe it) - A **KPI strip**: slow movers, promo markdowns, items flagged for clearance, deepest promo cut, average new margin. - **Top Sellers** and **Slow Movers** sections, each with an inline SVG bar chart (the slow-mover chart marks the weeks-of-cover threshold) and a sortable table. - A **Markdown Recommendations** section: a discount-depth chart, the policy chips, a sortable table showing current price, discount, new price, new margin, and the binding constraint, with **clearance-flagged** rows highlighted and a toggle to hide them. ## Report back Tell the manager the interactive report is ready (`merch_report.html`), that it opens in any browser, and that tables are sortable and clearance items can be toggled. Summarize the headline: how many promo markdowns, the deepest cut, and which items were routed to clearance. ## Notes - The bundled files are `merch_report.py` and `report_template.html.j2`; the script uses only the Python standard library plus **Jinja2** (available in the runtime). If the template file is missing it falls back to a minimal embedded template. - The report inlines everything - no CDN, no web fonts, no network. It is safe to share and open offline. - Never invent numbers - every figure comes from the analysis, optimizer, and Store Policy Agent results. All data is mock; for demo purposes only.