Separate the moving parts
Local capture, cloud transcription, hosted chat, and team sync are separate choices. Turning off a report’s schedule does not turn off recording or cloud transcription. A local recording also does not guarantee that an AI analysis stays local: the selected provider determines where its supplied context is processed.
Which allowance am I using?
Screenpipe Cloud chat and background scheduled tasks can share an account allowance. A task running in the background can therefore affect how much hosted chat remains available. External providers have their own policies and limits.
Account allowance and a model’s context window measure different things. Context usage describes how much information fits into that conversation; it is not your remaining monthly balance. Local token or cost estimates may cover only tracked sessions and need not equal the provider’s invoice.
Use the account’s current display for its allowance and reset information. This guide does not fix a plan price, token quantity, or reset schedule that may vary by account.
Review one task
Open Scheduled tasks → My tasks and select the task. Inspect its prompt, schedule, selected provider/model, and latest execution history. Then use this prompt with an assistant that can inspect that configuration:Control runs and schedules
Stopping does not undo completed writes or already consumed AI usage. Auto-run off does not close a client job or pause recording. Use scheduled task debugging if an execution remains stuck.
Warnings and spending limits
Versions with background allowance warnings can notify you when the service reports that scheduled tasks are consuming most of the hosted allowance. Delivery depends on the service response and notification preferences. These advisories are not a user-defined dollar cap or a guaranteed warning before every run. If you require a hard spending limit, verify the controls for the provider and account you are actually using. Writing “never spend more than $5” in an AI prompt does not create an enforced billing limit. Keep a workflow manual while its spending controls are unclear.Reduce repeated AI work
Start with one manual run over a short, known interval. Once accurate:- Match the frequency to when you need the output, such as one end-of-day report.
- Query only the relevant date, project, and apps. Keep a checkpoint so later runs process new evidence.
- Keep the output compact and preserve existing corrections instead of regenerating an entire knowledge base.
- Try a less expensive available model on the same example and compare accuracy.
- Inspect retries and failed runs. Repeated errors can consume usage without producing a useful artifact.