Agent skill · writing content · nousresearch
fitness-nutrition
Workout planning, macros, and body metrics via wger/USDA.
Why this skill is useful
Provides specific API commands and data structures for exercise and nutrition tracking that the AI wouldn't reliably generate on its own.
What it needs
Requires curl, python3 installed locally. Requires usda account access. About 5k tokens when loaded. Last updated 2026-08-07. 226,679 stars on the source repository.
What this skill does
Fitness & Nutrition Expert fitness coach and sports nutritionist skill. Two data sources plus offline calculators — everything a gym-goer needs in one place. Data sources (all free, no pip dependencies): wger (https://wger.de/api/v2/) — open exercise database, 690+ exercises with muscles, equipment, images. Public endpoints need zero authentication. USDA FoodData Central (https://api.nal.usda.gov/fdc/v1/) — US government nutrition database, 380,000+ foods. DEMOKEY works instantly; free signup for higher limits. Offline calculators (pure stdlib Python): BMI, TDEE (Mifflin-St Jeor), one-rep max (Epley/Brzycki/Lombardi), macro splits, body fat % (US Navy method) --- When to Use Trigger this skill when the user asks about: Exercises, workouts, gym routines, muscle groups, workout splits Food macros, calories, protein content, meal planning, calorie counting Body composition: BMI, body fat, TDEE, caloric surplus/deficit One-rep max estimates, training percentages, progressive overload Macro ratios for cutting, bulking, or maintenance --- Procedure Exercise Lookup (wger API) All wger public endpoints return JSON and require no auth. Always add format=json and language=2 (English) to exercise queries. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nousresearch/fitness-nutrition