Daytrace

Daytrace is a privacy-first desktop utility that turns a person's day into a searchable text journal. Screen, microphone, keyboard activity, and system context are independent opt-ins. Captured media is processed ephemerally and discarded; the durable record contains text and structured metadata only.

This repository now includes a headless ActivityWatch summary prototype. The broader cross-platform capture application remains in the product and architecture planning phase.

ActivityWatch summary prototype

The first executable prototype is a Python CLI that reads a selected day from an already-running ActivityWatch instance and produces deterministic Markdown. It does not copy raw events or call an LLM.

Prerequisites: install and run ActivityWatch, then install uv. On Windows:

winget install --id=astral-sh.uv -e

From a source checkout:

git switch codex/activitywatch-integration-research
uv sync
uv run daytrace activitywatch --date 2026-09-10 --output summary.md

Filter the report to records containing a project name:

uv run daytrace activitywatch --date 2026-09-10 --project daytrace --output summary.md

The resulting summary.md contains an overview, a chronological timeline, and application totals. A day with no matching activity is still a successful report and contains No matching activity.

After the package is published, the equivalent one-off command will be:

uvx daytrace activitywatch --date 2026-09-10 --output summary.md

Python callers—including a future second-brain integration—can use the same deterministic renderer directly:

from datetime import date

from daytrace.activitywatch import summarize_day

markdown = summarize_day(date(2026, 9, 10), project="daytrace")

Daytrace reads ActivityWatch through http://127.0.0.1:5600 by default. It does not retain images, audio, video, full browser URLs, or a second copy of ActivityWatch events. Use --server for another ActivityWatch endpoint and --timezone for an explicit IANA timezone such as America/Los_Angeles.

Product decisions

• Local-first: the database and processing stay on the user's computer unless the user explicitly configures a cloud provider or export destination.
• All capture sources start off and require separate, informed consent.
• Tauri 2 and Rust are the recommended desktop stack, with a small React/Vite interface that normally stays hidden behind a tray icon.
• Accessibility text is preferred over screenshots. OCR is a fallback, and image buffers are destroyed after extraction.
• Microphone audio is held only in bounded memory, segmented with voice activity detection, transcribed, and discarded.
• Keyboard capture defaults to activity signals only, not key content. An advanced typed-text mode is a later, separately consented feature with password and deny-list suppression.
• SQLite, B-tree time dimensions, and FTS5 provide the hierarchical timeline and full-text search. Captured media and vector embeddings are not stored.
• The first release supports BYOK and local providers. A hosted inference gateway can later fund the project without locking users into the service.

Plan

• Implementation plan
• Architecture
• Data model and search
• Privacy and security
• Product and UX specification
• Screenpipe reuse audit
• ActivityWatch integration research

Proposed repository shape

apps/
  desktop/                 Tauri window, tray, onboarding, settings
crates/
  daytrace-core/           orchestration, policies, domain events
  daytrace-capture/        platform-neutral capture traits
  daytrace-platform-*/     macOS, Windows, and Linux adapters
  daytrace-extract/        accessibility, OCR, VAD, transcription
  daytrace-store/          SQLite migrations, FTS, retention
  daytrace-summary/        segmentation and provider-neutral summaries
  daytrace-sync/           deterministic export and GitHub sync
  daytrace-secrets/        OS credential-store abstraction
extensions/
  browser/                 optional Chromium/Firefox tab metadata bridge
docs/

Target outcome

The v1 release is a signed, auto-updating macOS, Windows, and Linux desktop app that can run for an eight-hour day without retaining raw media, recover cleanly from sleep and device changes, search a local journal, and create an editable end-of-day summary. See the implementation plan for measurable release gates.