Parse Markdown workout logs to CSV and query history with DuckDB.
npx skills add https://github.com/mberg/claude-skills --skill fitness-tracker
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
Log workouts via conversation and save to GitHub; parse Markdown workout logs to CSV; and query exercise history with DuckDB to track progress.
Log a workout today to create an entry and update the CSV for quick analysis.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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.
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