Do I need SQL knowledge to see my progress?

While the skill uses DuckDB for analysis, you can use simple natural language prompts to have Claude run the necessary SQL queries for you to visualize your progress.

What happens if I make a typo in an exercise name?

The skill includes a validation step that checks your input against a reference list and suggests corrections for common typos to keep your data clean.

Can I add my own custom exercises?

Absolutely. You can expand the exercise list by editing the reference file to include your specific movements, categories, and validation rules.

How does the Fitness Tracker skill store my data?

It saves workout logs as Markdown files directly to a GitHub repository or a local Obsidian vault, ensuring you maintain full ownership and version control of your data.

Can I use natural language to record my sets?

Yes, you can enter sets naturally like '135 for 10, 10' or '30 minutes cardio', and the skill will automatically parse them into a structured format.

Fitness Tracker

Name: Fitness Tracker
Author: mberg

bymberg

Productivity & Workflow

Logs and analyzes workout data through conversational interfaces, version-controlled storage, and SQL queries.

About

The Fitness Tracker skill transforms Claude into a personal workout assistant that streamlines recording gym sessions via natural conversation. It automatically organizes workout data into Markdown files, synchronizes them with GitHub or Obsidian, and converts them into structured CSV formats for deep analysis. With integrated DuckDB support, users can run complex SQL queries to visualize progress, calculate total volume, and track personal bests over time without leaving the chat interface.

Key Features

Conversational workout logging with natural language set entry
Automatic GitHub and Obsidian synchronization for persistent data storage
0 GitHub stars
Advanced progress analysis using integrated DuckDB SQL queries
Markdown-to-CSV parsing with built-in exercise validation and typo correction
Customizable exercise reference library for personalized tracking

Use Cases

Analyzing historical lifting volume and strength trends over time using SQL
Recording gym sets, reps, and weights via chat during or after a workout
Maintaining a portable, version-controlled fitness journal in Markdown format

About

Key Features

Conversational workout logging with natural language set entry
Automatic GitHub and Obsidian synchronization for persistent data storage
0 GitHub stars
Advanced progress analysis using integrated DuckDB SQL queries
Markdown-to-CSV parsing with built-in exercise validation and typo correction
Customizable exercise reference library for personalized tracking

Use Cases

Analyzing historical lifting volume and strength trends over time using SQL
Recording gym sets, reps, and weights via chat during or after a workout
Maintaining a portable, version-controlled fitness journal in Markdown format