Ops Revenue

${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh snapshot 2>/dev/null || echo '{}'

USAGE_FILTER='{"Dimensions":{"Key":"RECORD_TYPE","Values":["Usage"]}}'
aws ce get-cost-and-usage \
  --time-period "Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d)" \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --filter "$USAGE_FILTER" \
  --group-by "Type=DIMENSION,Key=SERVICE" \
  --output json 2>/dev/null

USAGE_FILTER='{"Dimensions":{"Key":"RECORD_TYPE","Values":["Usage"]}}'
aws ce get-cost-and-usage \
  --time-period "Start=$(date -v-3m +%Y-%m-01 2>/dev/null || date -d '3 months ago' +%Y-%m-01),End=$(date +%Y-%m-%d)" \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --filter "$USAGE_FILTER" \
  --output json 2>/dev/null

${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh record-types 2>/dev/null || echo '[]'

aws ce list-savings-plans-purchase-recommendation --output json 2>/dev/null || echo '{}'
aws ce get-credits --output json 2>/dev/null || echo "credits API unavailable"

aws ce get-cost-forecast \
  --time-period "Start=$(date +%Y-%m-%d),End=$(date +%Y-%m-28)" \
  --metric "UNBLENDED_COST" \
  --granularity MONTHLY \
  --output json 2>/dev/null

cat "${CLAUDE_PLUGIN_ROOT}/scripts/registry.json" 2>/dev/null | jq '[.projects[] | {alias, name, stage: (.revenue_stage // .revenue.stage // "pre-revenue"), mrr: (.mrr // 0), source: (.source // "git"), type: (.type // "repo")}]'

${CLAUDE_PLUGIN_ROOT}/bin/ops-external 2>/dev/null || echo '[]'

# For each Shopify project in registry with valid credentials:
STORE_URL="[from project.shopify.store_url]"
TOKEN="[from env var named in project.shopify.credential_key]"
curl -s -H "X-Shopify-Access-Token: $TOKEN" \
  "https://$STORE_URL/admin/api/2024-10/orders.json?status=any&created_at_min=$(date -v-30d +%Y-%m-%dT00:00:00Z 2>/dev/null)&limit=250" 2>/dev/null

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 OPS ► REVENUE & COSTS — [month]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

AWS USAGE BURN (RECORD_TYPE=Usage — not credit-masked net)
 This month usage:    $[X]     ← from aws-usage-cost.sh mtd_usage
 Forecast (EOM pace): $[X]     ← eom_pace (7d Usage avg × days)
 Last month usage:    $[X]
 MoM change:          [+/-X%]
 7d avg/day:          $[X]

 Top services (Usage):
 [service]  $[X]  ([%] of usage)
 [service]  $[X]
 ...

CREDITS / MASK (do not report as low spend)
 Credits applied MTD:    $[X]  (record_types Credit)
 Discounts MTD:          $[X]
 Net after mask:         ~$0 is EXPECTED when credits cover burn
 Credits remaining:      $[X] (if API available)
 Expires:                [date]
 Months cover at pace:   [N]

REVENUE PIPELINE
 PROJECT        SOURCE     STAGE           MRR/GMV    STATUS
 ──────────────────────────────────────────────────────────────
 [project]      git        [stage]         $[X]       [status]
 [project]      shopify    [stage]         $[X] GMV   [status]
 [project]      custom     [stage]         $[X]       [status]
 ...
 ──────────────────────────────────────────────────────────────
 TOTAL MRR                                 $[X]
 TOTAL SHOPIFY GMV (30d)                   $[X]

RUNWAY ESTIMATE
 Monthly burn (AWS):  $[X]
 Total MRR:           $[X]
 Net burn:            $[X/month]
 Credits cover:       [N months]
 Cash runway:         [depends on external data]

──────────────────────────────────────────────────────

  [Drill into AWS costs by service]
  [Show cost anomalies (spike detection)]
  [Export cost report]
  [More...]

  [Update project revenue stage]
  [Set budget alert]

Write(file_path: "/tmp/ops-revenue-[date].md", content: "[formatted report]")