ARVO

Get history of training approaches tried: approaches used, duration, workouts completed.

get_approach_history

Get body-weight check-ins and weight trend over time, including check-in notes and cycle context.

get_body_progress

Get history of caloric phases: bulk, cut, maintenance with dates, duration, weight change.

get_caloric_history

Get recent cardio activities from external apps (Apple Health, Strava): running, cycling, swimming, walking.

get_cardio_activities

Get history of completed training cycles: cycle number, dates, stats, performance.

get_cycle_history

Get the user's notes on exercises. Can filter by exercise name.

get_exercise_notes

Get progression trend for a specific exercise: e1RM over time, weight, reps.

get_exercise_progress

Get exercise demonstration video from MuscleWiki. Returns video URLs for different angles (front, back, side). The lookup may refresh shared exercise caches and name mappings. Use when user asks for technique, form, or how to perform an exercise.

get_exercise_video

Get fitness summary from external apps (Apple Health, Strava, etc.): cardio load, sleep, recovery, weight.

get_fitness_summary

Get daily health metrics from external apps: steps, HRV, resting heart rate, active calories.

get_health_metrics

Get the user's personal records (PRs) for exercises: max weight, reps, estimated 1RM.

get_personal_records

Get the user's recently completed workouts with stats: duration, volume, sets, mental readiness.

get_recent_workouts

Get sleep data from external apps (Apple Health): duration, quality, sleep phases.

get_sleep_data

Get the user's fitness profile including name, age, experience level, training approach, weak points, equipment, caloric phase, and preferences.

get_user_profile

Get volume distribution (sets) by muscle group in the current cycle.

get_volume_by_muscle

Get the workout for a specific cycle day with full details: exercises, target weights, reps, RIR. If cycle_day is omitted, returns today's workout. Pass planned_date (user-local YYYY-MM-DD) when the user names a concrete calendar day: a standalone workout planned for that date is returned first. Input contract (properties, required) is served from the canonical support-chat tool definition.

get_workout_for_day

Get current workout progress including all logged sets and completion status.

get_workout_progress

Get aggregated workout statistics: total workouts, volume, sets, average duration, mental readiness, weekly frequency.

get_workout_stats

Log a completed set with actual weight and reps during a workout session.

log_set

Modify the active cycle structure by inserting or removing a rest day. Draft or ready workouts on shifted cycle days are deleted because their schedule is no longer valid.

modify_split_cycle

Persistently swap today's split session with the nearest session of the requested type, archive any stale current workout, and queue a replacement workout when needed.

override_today_session

Reorder exercises in today's workout.

reorder_exercises

Report pain, injury, or physical limitation to be considered in future workouts.

report_physical_issue

Save important information about the user for future conversations: preferences, limitations, patterns. To mark a physical limitation/injury as no longer in effect (healed/resolved), pass category="limitation" and status="resolved" with the title identifying the original condition — the backend archives the matching active limitation instead of adding a contradictory one.

save_memory

Skip an exercise in today's workout.

skip_exercise

Mark a workout as started and begin tracking time.

start_workout

Generate AI-suggested alternatives for an exercise in today's workout. This records AI usage against the account usage limits; it does not apply a replacement. Use apply_swap separately to change the workout.

swap_exercise

Update the user's caloric phase: bulk (muscle gain), cut (fat loss), or maintenance.

update_caloric_phase

Modify the user's available equipment.

update_equipment

Modify the user's weak points (muscles to emphasize in training).

update_weak_points