.claude/skills/run-race-predictor/SKILL.md
Predict race times for 5k / 10k / half marathon / marathon from the user's recent best efforts. Use when the user asks "for what time am I ready", "race predictor", "when can I run a sub-X".
npx skillsauth add AlvaroLaraFF/strava-coach run-race-predictorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Uses both:
T2 = T1 * (D2/D1)^1.06) anchored on the best recent effortBest efforts come from the local best_efforts table — backfilled from the
raw_json of each Run activity (Strava ships them per activity).
If best_efforts is empty, the script tries to backfill from stored activities
automatically.
python3 .claude/skills/run-race-predictor/scripts/race_predictor.py --recent-days 60
Show the anchor effort, then 4 predicted times (5k, 10k, HM, M) with both methods side by side. Add VDOT if computed.
python3 .claude/skills/athlete-snapshot/scripts/update_snapshot.py --source run-race-predictor --vdot <VDOT>
Replace <VDOT> with the computed value. Show alerts if any.
| Error contains | Action |
|---|---|
| No token / StravaAuthError | Invoke strava-setup, retry |
| best_efforts / Sync first / No best_efforts | Invoke strava-sync --level details --limit 50, retry |
| No activities / No runs | Invoke strava-sync --level summary, retry |
| anything else | Surface |
Chain at most ONCE.
Save a qualitative observation to memory — opinions, patterns, coaching notes. Never store raw numeric values (those are recomputable from the DB). Only write if the observation is NEW or CHANGED vs existing memory. See CLAUDE.md → Memory protocol.
data-ai
Show a weekly training log: activities grouped by ISO week and sport, with totals for distance, time and elevation. Use when the user asks "what did I do this week", "weekly summary", "training log".
tools
Cross-reference recent runs/rides with historical weather (temperature, humidity, wind) from Open-Meteo to find correlations with performance. Use when the user asks "do I run worse in the heat", "weather impact", "temperature vs pace".
testing
Show how the user's training time and volume distribute across run, ride and swim, and flag underweighted disciplines. Use when the user asks "am I balanced", "discipline balance", "which sport am I neglecting".
data-ai
Compute a combined CTL/ATL/TSB across run, ride and swim for triathletes. Use when the user asks "my combined load", "triathlon training load", "total TSS across sports".