Automatically tracks which apps you used, which websites you visited, and how much time you spent in each app throughout the day.
1.5k
Stars
95
Forks
4
Open issues
4
Contributors
AI Analysis
Work Review is a local-first desktop application (Rust + Tauri) that automatically tracks app usage, website visits, window titles, and time spent throughout the day, then organizes this data into a timeline for personal work review and daily report generation. It's purpose-built for individuals and knowledge workers who want to self-audit their work habits and generate structured daily summaries, with optional AI-powered analysis; it is not intended for employee surveillance or cross-device ...
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Privacy-first activity tracker built in Rust; local-only alternative to ActivityWatch with AI-optional daily reporting
Work Review is a personal activity tracking application designed for self-review rather than monitoring. It records foreground apps, browser pages, window titles, and usage time—stored locally in SQLite by default. The tool targets knowledge workers who want automated context capture for daily retrospectives and report generation. Optional AI integration (via user-configured models) supports Q&A over activity records. Created March 2026, it has gained 1,425 stars and 68 stars in the last 7 days as of June 2026, indicating early-stage traction among a privacy-conscious audience.
Work Review emerged in March 2026 as a newer entry in the personal activity tracking space, roughly 3 months old at analysis date. The space has established leaders (ActivityWatch ~18k stars since 2013, Dayflow ~6k stars), but this project explicitly targets local-first privacy and AI-optional design—distinguishing its positioning rather than directly copying existing approaches.
The project achieved 1,425 stars in ~3.5 months, averaging ~410 stars/month or ~66 stars/week. Recent 7-day velocity (68 stars) is strong for a newly published tool, suggesting sustained interest. Growth appears driven by positioning (privacy-first, local-only) and feature completeness at launch (timeline, reports, optional AI). Last push on 2026-06-28 indicates active maintenance through at least the analysis date.
Adoption not verified. No case studies, deployment numbers, or user testimonials documented in README. The tool is positioned for personal use only ('For personal use only — all data stays on your device'). No evidence of enterprise or team deployment. GitHub metrics (1,425 stars, 85 forks) suggest interest, but stars do not indicate actual installation or active use.
Likely a Rust desktop application using Tauri (mentioned in icon path src-tauri/icons/icon.png). README suggests local SQLite storage, per-app tracking, OCR/screenshot capture, and optional integration with multiple AI providers (Ollama, OpenAI-compatible, DeepSeek, Gemini, Claude, etc.). Supports macOS, Windows, Linux (X11/Wayland, x86_64/ARM64). Multi-language UI (English, Chinese simplified/traditional noted). Implementation details beyond README are not verifiable without source inspection.
Not documented in README.
Project is 3.5 months old (created 2026-03-10, last push 2026-06-28). Last push is 1 day before analysis date (2026-06-29), indicating very recent activity. Early-stage projects often have high commit velocity; this does not yet indicate long-term stability but does show active development.
ADOPT IF: you are an individual knowledge worker who wants automated daily context capture with strong privacy guarantees, are comfortable with a young codebase (3.5 months old), and either don't need AI or will self-host/pay for your own API. AVOID IF: you need production stability, long-term vendor commitment, team/enterprise features, or extensive community plugins and integrations. MONITOR IF: you value privacy and AI-optional design but want to wait 6–12 months for the project to mature, stabilize, and accumulate deployment evidence.
Independent dimensions
Mainstream potential
3/10
Technical importance
6/10
Adoption evidence
2/10
- Very early stage (3.5 months old); API, data schema, or feature priorities may shift without warning.
- Adoption not verified; no evidence of sustained production use or user retention beyond initial GitHub interest.
- Maintenance depends on a single apparent maintainer (wm94i); no visible governance or succession plan if developer loses interest.
- Platform coverage (macOS/Windows/Linux) is broad, but OS-specific permissions/APIs (e.g., screen recording on macOS, foreground app detection on Windows) may break with OS updates.
- Optional AI integration adds complexity; reliance on external LLM API providers introduces dependency risk and potential cost if user runs models.
Work Review will likely remain a niche but actively maintained tool for privacy-conscious individual users if the maintainer continues engagement. Growth may plateau as it reaches its target audience (personal-use, privacy-first segments), or accelerate if workplace privacy concerns drive adoption. Mainstream enterprise adoption is unlikely given explicit personal-use positioning.
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Languages
Information
- Website
- https://aiqst.com
- Language
- Rust
- License
- MIT
- Last updated
- 22h ago
- Created
- 4mo ago
- Analyzed with
- anthropic/claude-haiku-4-5
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Open issues
Open pull requests
No open pull requests.
Top contributors
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Established Python-based tracker (~18k stars, mature). Work Review differentiates via Rust implementation, explicit privacy framing, optional AI, and daily report generation; ActivityWatch is more extensible and has broader plugin ecosystem.
Swift-based, similar feature set (~6k stars). Work Review runs on Windows/Linux; Dayflow is macOS-focused. Work Review emphasizes AI-optional; Dayflow's positioning unclear from metadata.
Manual time tracking in C++ (~1.6k stars). Work Review is automatic; Timewarrior is manual. Fundamentally different use cases.
Commercial cloud-based tracker. Work Review is local-first, open-source, free; RescueTime is proprietary and cloud-centric.
Manual+cloud. Work Review is automatic and privacy-first; Toggl is team-focused and cloud-dependent.
