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Aggregates the past 7 days of completed workouts: total mileage, quality session adherence, fatigue indicators (RPE creep, HR drift). Decides hold/advance/recovery for the next week. Use for /run-week.
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Baseado na classificação ocupacional SOC
| name | weekly-review |
| description | Aggregates the past 7 days of completed workouts: total mileage, quality session adherence, fatigue indicators (RPE creep, HR drift). Decides hold/advance/recovery for the next week. Use for /run-week. |
Computes a structured summary of the past training week by comparing workouts.json actuals against plan.json prescriptions for that week number. The deterministic aggregation (volume, quality counts, RPE creep, HR drift) runs in scripts/weekly.py. Claude renders the results as a human-readable report and, if the verdict is recovery, triggers adapt-plan to insert a recovery week.
/run-week (optionally with --week N; defaults to the current plan week).A weekly summary dict appended to storage/progress.json.weekly_summaries and a Markdown report displayed to the user. If verdict is recovery, plan.json is also modified via adapt-plan.
See body.md for full instructions and scripts/weekly.py for the aggregation logic.
Applies 1/2/3-strike adjustment rules to plan.json based on a single workout's analysis dict. Mutates plan only when thresholds fire. Called after every workout log.
Renders today's workout card from plan.json and daily_state.json as a Markdown block. Use for every /run-today invocation. No writes — pure read-and-render.
Conversationally captures a completed workout (duration, distance, RPE, HR, splits, notes) and writes it to workouts.json. Triggers analyze-workout and adapt-plan downstream. Use for /run-log.
Inserts a post-race or injury-flag recovery block into plan.json: 4 days rest + 3 easy jog days (post-race), or 3 rest + 1 recovery (red-flag-fatigue), or 7 rest days (injury). Use after /run-race-recap or when adapt-plan returns red_flag_recovery.
Web-search-backed Q&A for novel coaching questions outside the plan's standard logic: heat acclimation, recovery from illness, pacing strategies for unique courses. Use for /run-research and when the Coach cannot answer from training data alone.
Pulls recent run activities from the garmin-givemydata MCP server: triggers garmin_sync to refresh the local SQLite, queries activity IDs in the requested date range, fetches per-activity detail (with splits, HR zones, weather, running dynamics), normalizes to workouts.json schema via garmin_normalize.py, deduplicates by garmin_activity_id with preferred_source tiebreaker, and runs the same analyze-workout + adapt-plan pipeline as manual logging. Requires users.integrations.garmin.connected = true.