5 Must have Logseq simple queries

Logseq’s “simple queries” turn scattered notes into instant, filterable dashboards by leaning on page properties and a handful of query operators. The core idea behind the five must-have queries is consistent: store structured metadata on pages (like type, author, tags, links, or habit fields), then build views that automatically pull the right pages into tables or focused lists—without manually searching every time.

The first and most reusable pattern is a page-property overview. A single “type” page (for example, a Book type page) acts as a hub, while each item page links back to that hub through a property such as type. From there, a query can search for pages where a given property matches a specific type value, producing a clean table. To make this scalable, the workflow pairs the hub page with a template: the template defines the fields to collect (author, state, tags, series, and other book-related properties) and provides default structure. When a new item is added, inserting the template into a journal line and clicking the type link automatically routes the user to the correct overview.

The second query targets task triage using tags and the AND operator. A “shopping list” example shows how tasks can be filtered to only those marked as to-do, then further narrowed to a specific tag (like a Dutch supermarket tag). The result is a phone-friendly list that updates as new tasks are created—ideal for real-world workflows where you need a quick, context-specific view.

Third, filtered text views for writing and planning rely on tag intersection with the current page. By using the amp operator, the query can pull every line that contains both a specific tag (like “Boll”) and the current page context. For templates, the current page macro is recommended, but it comes with a caveat: zooming changes the current page variable, which can break the query.

Fourth, personal “people” overviews come from linking plus tags. When sections are marked with links to coworkers and tagged appropriately, a query can fetch all matching journal entries—then use copy-as to send quick reminders containing only the relevant tasks for that person. To avoid template sprawl, templates can be stored in separate files and retrieved dynamically via a template property, so the system stays organized even as the library grows.

Finally, habit tracking becomes a daily input plus a weekly summary. By adding an hours (or other measurable) property to a journal template and then querying for all journal pages that contain that property, the system generates an overview sorted by created time. That turns what would be a manual weekly bookkeeping job into a near-instant routine.

Taken together, these five queries show how Logseq’s property-based structure—type hubs, tag filters, current-page scoping, link-and-tag retrieval, template fetching, and property-driven habit summaries—can compress frequent tasks into seconds while keeping notes consistent and searchable across devices.