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mickpletcher
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fitness-log

Convert workout data into training logs, trend summaries, and goal checks.

14|2|Updated Apr 24, 2026
Search Tags:#weekly review#goal tracking#workout logging#fitness planning#training trends#benchmark history#structured export
One-click install
npx skills add https://github.com/mickpletcher/AI-Skills --skill fitness-log
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fitness-log
Source: https://github.com/mickpletcher/AI-Skills/tree/main/claude/skills/fitness-log
Command: npx skills add https://github.com/mickpletcher/AI-Skills --skill fitness-log

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps athletes turn raw workout notes into actionable fitness tracking, including progress comparisons, fatigue/overload flags, and weekly planning grounded in the user’s logged evidence.

Core Features & Use Cases

  • Workout logging and PR capture: Records sessions with normalized exercise naming and highlights regressions or unusual patterns.
  • Progress, trends, and goal checks: Summarizes strength, endurance, consistency, and recovery trends and compares recent training to stated targets.
  • Planning and export outputs: Produces weekly reviews and longer-horizon plans, plus export-friendly dashboard, notes, or weekly report structures, and can generate Facebook posts from workout data.

Quick Start

Use the fitness-log skill to log a workout and summarize trends for the last two weeks by sending: "fit summarize my strength and recovery trends from the last 2 weeks".

Frequently Asked Questions about fitness-log

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

FAQPage Schema
How do I log workouts and generate progress trend summaries?▼

Workout logging converts raw fitness data into normalized exercise records, then generates trend summaries by comparing recent training against baseline benchmarks and stated goals.

What is the best way to track PR milestones and flag training fatigue?▼

PR milestone tracking updates benchmark history from session data, while fatigue flagging analyzes logged workout evidence to highlight regressions, unusual patterns, or overload.

Can I generate weekly fitness reviews and long-horizon training plans from raw notes?▼

Weekly review generation transforms raw workout notes into structured summaries, while instruction-driven workflows produce long-horizon program adjustments grounded in your logged evidence.

Do I need a YAML identity file to use automated workout logging?▼

Yes, the workout logging workflow requires a YAML-defined identity to normalize exercises, compare against benchmarks, and follow structured output formats for planning and reporting.

How do I export training logs for dashboards or write social posts from workout data?▼

Export-friendly reporting structures convert training logs into dashboard notes, and the skill can generate Facebook posts directly from your normalized workout data and progress summaries.

When should I not use automated fitness logging for program adjustments?▼

Avoid automated program adjustments when raw workout notes lack sufficient detail, because fatigue and overload flags are generated only from concrete evidence within your logged training data.

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