Dayflow

What

Dayflow is a native macOS app that automatically records on-screen activity and turns it into a timeline of how the day was spent. It is designed for developers, freelancers, and other knowledge workers who want an automated, more truthful record of focus time, interruptions, and task patterns without manually tagging work.

The product is positioned as a private, open-source alternative to traditional time trackers. Its core workflow is simple: it captures screens periodically, analyzes activity with AI, and presents context-aware summaries that distinguish between deep work, shallow tasks, breaks, and distractions. On the source page, the strongest emphasis is on local storage, privacy controls, and contextual understanding rather than billing, team management, or enterprise administration.

Features

• Automatic screen-based activity capture: Dayflow records the screen at 1 frame per second so users can build a passive record of work without manual time entry.
• Context-aware AI analysis: It analyzes activity every 15 minutes to identify what the user was likely doing, which helps separate productive research from unrelated browsing.
• Visual daily timeline: A color-coded timeline shows deep work, shallow tasks, and breaks at a glance, making patterns easier to review.
• Question-based activity lookup: The product supports queries such as how often Slack interrupted work or how long a report took, which makes retrospective analysis more practical.
• Privacy-first deployment options: In local mode, analysis can run fully on-device and recordings/databases remain stored locally on the Mac.
• Recording controls and automation hooks: Users can start or stop recording from the menu bar and automate control with Shortcuts via deeplinks.

Helpful Tips

• Validate privacy mode carefully: If strict data residency matters, use the local AI setup; the page states that cloud providers such as Gemini, ChatGPT, or Claude send data to those providers for analysis.
• Match model choice to workload: Cloud models are described as generally higher quality for accuracy and narrative detail, while local models may better fit users prioritizing offline use and control.
• Plan for device impact in offline setups: The page says capture is lightweight, but local AI inference can use more GPU and battery, so long sessions may work better while plugged in.
• Use it as a review layer, not a full operations system: The website supports personal activity understanding well, but it does not present evidence of broader project accounting, invoicing, or team analytics.
• Test interruption and focus categories against real work habits: Since the value depends on context detection quality, a short pilot can help determine whether the classifications are useful for a specific role.

OpenClaw Skills

Dayflow could likely fit well into the OpenClaw ecosystem as a source of personal work-context data for agents focused on productivity analysis, work journaling, and routine optimization. A likely workflow would be an OpenClaw skill that ingests Dayflow summaries or exported local records, then produces end-of-day briefings, interruption reports, weekly focus trend analyses, or manager-safe summaries that preserve sensitive screen content by abstracting it into categories rather than raw captures. The source page does not describe a native OpenClaw integration, so this should be treated as an inferred use case.

For developers, consultants, and other knowledge workers, the combination could support agents that correlate Dayflow activity with task systems, notes, or calendars to identify where work gets fragmented and where deep work actually happens. In a likely future workflow, OpenClaw could orchestrate a “personal operating review” agent that turns Dayflow’s timeline into coaching prompts, project postmortems, or habit-change experiments. Used carefully, that could shift personal analytics from passive tracking toward active workflow design, especially for solo professionals who need evidence-based ways to improve focus without adopting heavier enterprise software.