Data Flow

Runtime Flow

The practical flow in the @life-manager/db package:

query state
  -> action hook
  -> workflow resolution
  -> mutation enforcement
  -> local DB write
  -> sync layer

Table	Key Fields
`work_project`	title, salary, currency, folder_id, color
`work_folder`	title, parent_folder (hierarchical)
`work_time_entry`	start_time, end_time, project_id, paid
`work_project_tag`	project-tag mapping

Table	Key Fields
`appointment`	title, start_date, end_date, status (optionally linked to work)

Table	Key Fields
`bank_account`	title, currency, saldo
`single_cashflow`	amount, date, bank_account_id, contact_id, tag_id
`recurring_cashflow`	amount, interval, start_date, bank_account_id
`finance_project`	title, start_amount (groups related cashflows)
`finance_project_adjustment`	adjustments to finance projects
`finance_project_tag`	project-tag mapping

Table	Key Fields
`tag`	reusable tags for categorization
`contact`	contacts for transactions

Table	Key Fields
`profiles`	id, username, full_name, email, avatar_url
`notification`	system notifications

What	Import from
PowerSync schema (`AppSchema`)	`@life-manager/db/schema`
Supabase types (`Tables`, `Enums`, `Constants`)	`@life-manager/db/supabase`
Domain types	`@life-manager/db/types/work`, `@life-manager/db/types/finance`, `@life-manager/db/types/system`
Query hooks	`@life-manager/db/hooks/queries/*`
Action hooks	`@life-manager/db/hooks/actions/*`
Mutation hooks	`@life-manager/db/entities/<domain>/<entity>`
Zod schemas	`@life-manager/db/schemas`

Platform	Package	SQLite Backend
Web	`@powersync/web`	wa-sqlite
Mobile	`@powersync/react-native`	@powersync/op-sqlite

Both share the schema from @life-manager/db/schema.