I’ve been building Domestique, a free and open-source cycling training planner, and I’d love feedback or contributions from people who actually train with power.
The itch I was scratching: most “smart” planners stop at a dashboard — they show you CTL/ATL/TSB and leave the thinking to you. I wanted something that closes the loop: build the plan, ride it, import the ride, and have it mutate tomorrow’s prescription from what the ride actually showed — TSS overshoot, polarisation breach, DFA α1, aerobic decoupling, monotony, eFTP drift, daily-wellness.
What it does:
- Plans from your goal and your event. Pick an FTP or VO2max focus and it schedules more of the work that actually moves that number (threshold/sweet-spot vs VO2/30-15). Set a target event and it builds backwards from the date — a long-ride progression sized to the event’s distance + elevation, a fitness target that auto-lowers if the date’s too soon (so it never prescribes an impossible ramp), and climbing-specific work for hilly routes.
- ~4,200 structured workouts, copyright-free, content-classified (every file run through a classifier so the type/duration always matches the title), plus 600+ real-world route courses.
- Fully science-based. Every threshold and guardrail traces to the literature (Seiler, Rønnestad, Coggan, Gabbett, Mujika…), cited inline in the README — if you disagree with a number, the paper is right there.
- Computes DFA α1 in-ride — your aerobic threshold (HRVT1) straight from your chest strap’s RR/HRV data, with Malik artifact rejection and a per-ride α1-over-time chart. No lab, no ramp test.
- Reads your physiology, not just TSS: DFA α1 + HRV thresholds, intensity distribution, aerobic decoupling, monotony — and a morning readiness score that folds in your Garmin sleep + overnight HRV (synced through intervals.icu’s wellness).
- Integrated with [intervals.icu](https://intervals.icu) — one API key, no separate account; it pulls your rides, wellness, Garmin sleep + resting HRV automatically.
- Hardware-agnostic. Generate a ZWO or FIT; load it into a trainer app (MyWhoosh / Tacx / Zwift / Golden Cheetah) or push it straight onto a Garmin / Wahoo / Hammerhead; ride; import the FIT back to close the loop.
- Multiple profiles possible, localhost-only. No telemetry, no cloud, no subscription. Your data stays on your machine.
It’s free and open-source (MIT), and I’d genuinely welcome contributors — sports scientists, cyclists, and devs alike. The training logic is grounded in the literature (Seiler, Rønnestad, Coggan, Gabbett…) with inline citations in the README, so if you disagree with a threshold, the receipts are right there to argue with.
Honest disclosure: it’s a personal project, macOS + Windows, and a lot of it was built with heavy AI assistance — so it’s improved fast but I’m sure there are rough edges. That’s exactly what I’m hoping you’ll find.
Happy to answer anything about the methodology or take feature requests / PRs.