Review and analyze running training data from Strava. Query activities, intervals, pace trends, heart rate data, and gear mileage via the strava CLI. Use when asked about running workouts, training load, interval performance, weekly summaries, or fitness trends.
Query and analyze running data from a local SQLite database synced from Strava. All data is local — no live API calls needed during analysis.
Run strava <command> in the shell. All commands return structured JSON:
{"ok": true, "data": ..., "meta": {...}} // success
{"ok": false, "error": "...", "hint": "..."} // error
| Task | Command |
|---|---|
| Latest activities | strava query activities --limit 5 |
| Activity detail | strava query activity <id> |
| Activity with laps | strava query activity <id> --include laps |
| Detect intervals | strava query intervals <id> |
| Compare workouts |
strava query compare --activity-ids 111,222 |
| Weekly summary | strava query summary --period week --weeks 4 |
| Pace trends | strava query trends --metric average_speed --period month |
| Shoe mileage | strava query gear |
| Search by name | strava query search --name "tempo" |
| Sync status | strava query status |
| Add a note | strava note set <id> "Great session" |
| Export markdown | strava export activity <id> |
M:SS/km (e.g. 4:41/km)distance_m); summaries include total_distance_kmmoving_time_s, elapsed_time_s)average_speed); use avg_pace for human-readable paceRun, TrailRun, Walk, Hike, VirtualRun