weekly-load-review

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Review weekly training load against the rolling baseline and deliver a coaching summary.

AI & Automation 74 stars 15 forks Updated today MIT

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# Weekly Training Load Review ## Goal Pull the last 14 days of Strava activities and compute weekly training load summaries for this week (Mon–Sun) and the prior week (Mon–Sun). Compare against the 4-week rolling baseline stored in `state/strava-weekly-baselines.json` (create if missing). ## Steps 1. Call `mcp__strava__check-strava-connection`. If disconnected, alert the operator via the configured channel and stop. If no channel is configured, pipe the disconnection into `.claude-code-hermit/bin/hermit-run task note .claude-code-hermit <id>` only inside an open record's turn (otherwise skip the note) and stop. 2. Call `mcp__strava__get-recent-activities` with `perPage: 30` to cover 14+ days. 3. Determine the two week boundaries: this week is the most recent Mon–Sun period ending today (Sunday); the prior week is the Mon–Sun before that. Compute the exact date ranges from today's date. 4. For each week compute: - Run: total distance (km), total elevation (m), session count - Bike: total distance (km), session count - Strength: session count, total duration in minutes as `strength_minutes` (sum `moving_time` over WeightTraining/Workout activities: already in the Step 2 payload, no extra call; `moving_time` is in seconds, so divide the sum by 60) - Total active days Also compute **load-adjusted run distance** (`adjusted_km`): for each run activity, derive `elev_gain_per_km = elevation_gain_m / distance_km` and apply a heuristic multiplier to account for...

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Author
gtapps
Repository
gtapps/claude-code-hermit
Created
6 months ago
Last Updated
today
Language
TypeScript
License
MIT

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