Build a daily or weekly worklog from recorded activity and checked outcomes. Separate plans, observed work, and verified completion, then summarize useful results and unfinished tasks with source links and clearly marked gaps or estimates.
Reconstruct a daily or weekly worklog from observed activity and outcomes.
Review the instructions the agent will receive before you install.
Resolve the local dates and timezone. Read screenpipe-api and start with the activity summary. Use authoritative active minutes, never frame counts, to discuss time. Verify important outcomes with narrow source queries. Separate planned work, observed work, and externally verified completion. Do not count background agent runs as human effort. Return useful outcomes, unfinished work, and a few source links. Label estimates and coverage gaps. Keep raw chats, private identifiers, and unrelated activity out of the summary.
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Develop and test Windows-specific Screenpipe changes on a disposable Azure virtual machine. The workflow verifies native behavior, preserves logs and desktop video, and handles branch and pull request delivery when authorized.
Prepare screenpipe component releases by updating versions and dependency lock files, running required build checks, and triggering GitHub Actions. Verify build results and release artifacts, then hand public app publication over to a person.
Create charts, dashboards, scorecards, and styled summaries as standalone HTML reports for the screenpipe viewer. Keep styles, scripts, and images inside the file so the report renders in a sandbox with no network access.
Search Screenpipe recordings, screen text, audio transcripts, and synced-device history through its local API. Use the evidence to review activity, find meeting details, and inspect saved workflows, including recorded steps that can inform automation.
Use Screenpipe’s local REST API, an interface for programmatic requests, to search screen and meeting history, review app activity and active time, retrieve synced-device records, export recordings, and rerun audio transcription.
Turn a recorded software failure into a draft bug report with timestamps, reproduction steps, expected and actual behavior, and relevant evidence. Separate visible symptoms from possible causes and remove sensitive details from shareable evidence.