Workout Tracker A skill to log and track fitness activities using a local SQLite database. Capabilities Log Workout: Record exercise details. View History: See past performance. Smart Rest Time: Auto-fills rest time based on previous sessions if not provided. Visual Recognition: Can identify gym equipment from images to suggest exercises. Usage 1. Logging a Workout When the user says "I did 5 sets of Bench Press at 60kg for 8 reps", parse the details and run: cd skills/workout-tracker/scripts && uv run log.py \ --exercise "Bench Press" \ --weight 60 \ --unit kg \ --sets 5 \ --reps 8 \ --body_part "Chest" \ --rest_time 90

Optional: User provided or leave empty to auto-fill

--notes

"Optional notes"

Parameters:

--exercise

(Required): Name of the movement.

--body_part

:

(New)

Target muscle group (e.g. Chest, Back, Legs).

INFER THIS

from the exercise if not provided (e.g. Bench -> Chest).

--weight

(Required): Weight value.

--unit

'kg' or 'lb' (default kg).

--sets

Number of sets.

--reps

Reps per set.

--rest_time

Seconds.

OMIT THIS if the user didn't specify.

The script will auto-fill from history.

2. Viewing History

When the user asks "How is my Squat progress?" or "Show last workouts":

cd

skills/workout-tracker/scripts

&&

uv run render.py

--exercise

"Squat"

Then send the generated image:

message(action="send", filePath="/tmp/workout_report.png", message="Here is your report:")

3. Image Recognition (Vision)

If the user uploads an image (e.g., of a machine):

Analyze the image

using your vision capabilities.

Identify the equipment

(e.g., "Leg Press Machine", "Dumbbells").

Ask the user:

"This looks like a Leg Press. Do you want to log a set? How much weight?"

Once they reply, use the

log.py

script as usual.

Design & Behavior Rules (User Preferences)

1. User Profile

Type:

General User (Casual).

Interaction:

Use natural language.

Automatically infer

the

body_part

from the exercise name (e.g., "Bench Press" -> "Chest") without asking, unless ambiguous.

2. Display Format (Mobile Portrait)

Preferred Output:

Always generate an

Image

for reports using

render.py

.

Style:

Vertical (Portrait) aspect ratio optimized for mobile screens.

Layout:

Narrow width (

figsize

width ~6).

Wrap long text in "Notes" column.

Hide "Exercise" column if filtering by a single exercise (title context is enough).

Sort chronologically (Oldest -> Newest) within the day/session.

3. Logging Logic

Drop Sets:

Must be logged as

separate rows

for data accuracy.

Rest Time:

Set to

0

between drop set segments.

Notes:

Mark as "Drop set part X/Y" for clarity.

Units:

User prefers

lb

(pounds).

Database

Data is stored in

skills/workout-tracker/workout.db

(SQLite).

The schema includes

date

,

exercise

,

weight

,

unit

,

sets

,

reps

,

rest_time

,

notes

.

Technical Setup (Maintenance)

This skill uses

uv

for Python package management.

Installation

Ensure

uv

is installed:

brew install uv

Sync dependencies:

cd

skills/workout-tracker/scripts

uv

sync

Database Schema (SQLModel)

The SQLite database (

workout.db

) uses the following schema:

id

Integer (PK)

date

ISO8601 String

exercise

String

body_part

String (Target muscle group)

weight

Float

unit

String (default "kg")

sets

Integer

reps

Integer

rest_time

Integer (Seconds, optional)

notes

String (Optional)