Logseq Time Tracking: Basics and Examples

Logseq time tracking works by attaching time to task status changes—when a task moves into “doing,” Logseq records the start time, and when it moves out to “done” (or back to “to do”), it logs the finish time and duration. The practical payoff is that time totals emerge from your workflow without needing a background timer; the system simply writes timestamps when you switch task states.

In daily use, tasks live in a structured journal setup: a “day plan” area for fixed events like meetings (so they don’t clutter time logs), plus a “tasks” area where work items are copied in and linked to their source references. As work begins, the user updates a task’s status to “doing” (for example, “writing email to X” with details). When the work is interrupted or completed, the task is switched back to “to do” or moved forward to “done.” Each switch creates logbook entries that include start, finish, and duration; multiple work sessions on the same task produce multiple entries, and the displayed duration increases after each additional “doing” period.

Those logbook entries can be skimmed quickly via a small UI element at the end of the task, but if it doesn’t appear reliably, reloading the page resolves it. For deeper inspection, the logbook can be opened in a default app (such as code or a text editor) to view the full entry details. The workflow also supports resuming work: if the user returns later, they can locate the correct task using its unique ID—either by copying it from existing entries/task lists or by using clipboard history tools (Windows V key, with a similar approach on Linux). Once the correct task is found, switching it back to “doing” continues the time accumulation, and moving it to “done” preserves the newly added seconds.

After collecting many task-level time entries, the next step is turning them into project totals. This is done with a Logseq query that filters for tasks with specific statuses (“to do,” “doing,” “done”) and a project tag (e.g., “project Time Track”). The query outputs a table where tasks appear on the left and time aggregates appear on the right, with total time summarized at the top—enabling straightforward reporting like “six hours total” for a project once work is complete.

Two practical pain points and workarounds stand out. First, missed time tracking can be corrected by opening the logbook entry in the default app and editing the duration; Logseq then updates the displayed totals, though it’s somewhat cumbersome. Second, exporting time data for other tools may require conversion: one approach uses regex101 to transform copied log entries into a comma-separated format suitable for importing into tools like Toggle. The overall message is that Logseq time tracking is lightweight during execution, then powerful when paired with queries and occasional data conversion hacks for downstream reporting.