logseq-server-usage-stats

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Collect, interpret, and troubleshoot db-sync server usage stats (total users/graphs, active users/graphs in N days, created-today metrics) using the `deps/db-sync` scripts and D1 schema. Use when requests involve `show-usage-stats`, server usage reporting, active-entity counting, or Cloudflare D1 cost impact of usage tracking.

logseq By logseq schedule Updated 5/4/2026

name: logseq-server-usage-stats description: Collect, interpret, and troubleshoot db-sync server usage stats (total users/graphs, active users/graphs in N days, created-today metrics) using the deps/db-sync scripts and D1 schema. Use when requests involve show-usage-stats, server usage reporting, active-entity counting, or Cloudflare D1 cost impact of usage tracking.

Logseq Server Usage Stats

Use this skill to run and explain server usage stats for db-sync.

Run stats

Use the packaged command from deps/db-sync:

cd deps/db-sync
pnpm show-usage-stats
pnpm show-usage-stats --days 7
pnpm show-usage-stats --json
pnpm show-usage-stats --env staging --days 30 --json
pnpm show-usage-stats --env local --json

Metric semantics

Interpret output with these rules:

  • active_users_last_n_days and active_graphs_last_n_days come from deduplicated rows in daily_active_entities.
  • active_since_utc and today_utc are UTC-day boundaries.
  • users_created_today reads users.created_at in today UTC range.
  • graphs_created_today reads graphs.created_at in today UTC range.

When discussing data quality, explicitly mention:

  • activity is counted from request-path touch logic, not client app foreground time
  • active metrics are per day per entity, not per request

Cost review workflow

When asked about Cloudflare cost impact:

  1. Separate one-off stats query cost from continuous request-path tracking cost.
  2. Treat request-path activity touch as the primary D1 cost driver.
  3. Verify whether touch happens only on successful responses in the current code.
  4. Estimate cost with traffic shape:
    • successful sync request volume
    • unique (day, entity_type, entity_id) volume
    • cache effectiveness under multi-isolate execution
  5. Recommend reducing write attempts before adding new infrastructure:
    • keep touch only on meaningful successful routes
    • avoid duplicate touch points on read-heavy endpoints

Troubleshooting

If command fails, check in order:

  1. Wrong environment or wrangler config path.
  2. Missing migrations/tables/columns.
  3. D1 auth/project context mismatch.
  4. Non-integer --days value (>= 1 required).
Install via CLI
npx skills add https://github.com/logseq/logseq --skill logseq-server-usage-stats
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