fitness-tracker

Parse Markdown workout logs to CSV and query history with DuckDB.

Updated Oct 30, 2025

Search Tags:#markdown #analytics #csv #workout #duckdb #parse

Ready to run

npx skills add https://github.com/mberg/claude-skills --skill fitness-tracker

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: fitness-tracker
Source: https://github.com/mberg/claude-skills/tree/main/skills/fitness-tracker
Command: npx skills add https://github.com/mberg/claude-skills --skill fitness-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires duckdb, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Log workouts via conversation and save to GitHub; parse Markdown workout logs to CSV; and query exercise history with DuckDB to track progress.

Core Features & Use Cases

Log workouts via chat and save to GitHub.
Parse Markdown workout logs to CSV using the parse_workout.py tool.
Query exercise history and analyze progress with DuckDB.

Quick Start

Log a workout today to create an entry and update the CSV for quick analysis.

Frequently Asked Questions about fitness-tracker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I parse Markdown workout logs into CSV for analysis?▼

To parse Markdown workout logs into CSV, use the parse_workout.py tool to structure raw exercise entries, producing a validated CSV file ready for long-term trend analysis and performance insights.

Can I query exercise history with DuckDB to track workout progress?▼

Yes, you can query exercise history with DuckDB by loading the parsed CSV output, enabling fast aggregations and comparisons to track long-term workout progress and performance trends.

How do I log workouts via chat and save them to GitHub?▼

You can log workouts via chat by entering exercise details conversationally, which creates a Markdown entry and updates the CSV output for seamless saving to GitHub repositories.

Does this workout analytics approach work with Obsidian Markdown files?▼

Yes, this approach works with Obsidian Markdown files by parsing existing workout logs and validating them against a known exercise reference before converting them to structured CSV data.

What's the best way to analyze long-term fitness trends from Markdown logs?▼

The best way to analyze long-term fitness trends from Markdown logs is converting them to CSV and running DuckDB queries, enabling easy comparisons and performance insights across historical data.

Do I need DuckDB installed to query my parsed workout CSV data?▼

Yes, DuckDB is a required dependency to query parsed workout CSV data, providing the analytical engine needed to aggregate exercise history and generate long-term performance insights.