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| name | fitness-nutrition |
| description | Workout planning, macros, and body metrics via wger/USDA. |
| platforms | ["linux","macos","windows"] |
| version | 1.0.0 |
| author | Hailey Marshall (haileymarshall), Hermes Agent |
| authors | ["haileymarshall"] |
| license | MIT |
| metadata | {"hermes":{"tags":["health","fitness","nutrition","gym","workout","diet","exercise"],"category":"health","prerequisites":{"commands":["curl","python"]}}} |
| required_environment_variables | [{"name":"USDA_API_KEY","prompt":"USDA FoodData Central API key (free)","help":"Get one free at https://fdc.nal.usda.gov/api-key-signup/ — or skip to use DEMO_KEY with lower rate limits","required_for":"higher rate limits on food/nutrition lookups (DEMO_KEY works without signup)","optional":true}] |
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):
DEMO_KEY works instantly; free signup for higher limits.Offline calculators (pure stdlib Python):
Trigger this skill when the user asks about:
All wger public endpoints return JSON and require no auth. Always add
format=json and language=2 (English) to exercise queries.
Step 1 — Identify what the user wants:
/api/v2/exercise/?muscles={id}&language=2&status=2&format=json/api/v2/exercise/?category={id}&language=2&status=2&format=json/api/v2/exercise/?equipment={id}&language=2&status=2&format=json/api/v2/exercise/search/?term={query}&language=english&format=json/api/v2/exerciseinfo/{exercise_id}/?format=jsonStep 2 — Reference IDs (so you don't need extra API calls):
Exercise categories:
| ID | Category |
|---|---|
| 8 | Arms |
| 9 | Legs |
| 10 |
| Abs |
| 11 | Chest |
| 12 | Back |
| 13 | Shoulders |
| 14 | Calves |
| 15 | Cardio |
Muscles:
| ID | Muscle | ID | Muscle |
|---|---|---|---|
| 1 | Biceps brachii | 2 | Anterior deltoid |
| 3 | Serratus anterior | 4 | Pectoralis major |
| 5 | Obliquus externus | 6 | Gastrocnemius |
| 7 | Rectus abdominis | 8 | Gluteus maximus |
| 9 | Trapezius | 10 | Quadriceps femoris |
| 11 | Biceps femoris | 12 | Latissimus dorsi |
| 13 | Brachialis | 14 | Triceps brachii |
| 15 | Soleus |
Equipment:
| ID | Equipment |
|---|---|
| 1 | Barbell |
| 3 | Dumbbell |
| 4 | Gym mat |
| 5 | Swiss Ball |
| 6 | Pull-up bar |
| 7 | none (bodyweight) |
| 8 | Bench |
| 9 | Incline bench |
| 10 | Kettlebell |
Step 3 — Fetch and present results:
# Search exercises by name
QUERY="$1"
ENCODED=$(python -c "import urllib.parse,sys; print(urllib.parse.quote(sys.argv[1]))" "$QUERY")
curl -s "https://wger.de/api/v2/exercise/search/?term=${ENCODED}&language=english&format=json" \
| python -c "
import json,sys
data=json.load(sys.stdin)
for s in data.get('suggestions',[])[:10]:
d=s.get('data',{})
print(f\" ID {d.get('id','?'):>4} | {d.get('name','N/A'):<35} | Category: {d.get('category','N/A')}\")
"
# Get full details for a specific exercise
EXERCISE_ID="$1"
curl -s "https://wger.de/api/v2/exerciseinfo/${EXERCISE_ID}/?format=json" \
| python -c "
import json,sys,html,re
data=json.load(sys.stdin)
trans=[t for t in data.get('translations',[]) if t.get('language')==2]
t=trans[0] if trans else data.get('translations',[{}])[0]
desc=re.sub('<[^>]+>','',html.unescape(t.get('description','N/A')))
print(f\"Exercise : {t.get('name','N/A')}\")
print(f\"Category : {data.get('category',{}).get('name','N/A')}\")
print(f\"Primary : {', '.join(m.get('name_en','') for m in data.get('muscles',[])) or 'N/A'}\")
print(f\"Secondary : {', '.join(m.get('name_en','') for m in data.get('muscles_secondary',[])) or 'none'}\")
print(f\"Equipment : {', '.join(e.get('name','') for e in data.get('equipment',[])) or 'bodyweight'}\")
print(f\"How to : {desc[:500]}\")
imgs=data.get('images',[])
if imgs: print(f\"Image : {imgs[0].get('image','')}\")
"
# List exercises filtering by muscle, category, or equipment
# Combine filters as needed: ?muscles=4&equipment=1&language=2&status=2
FILTER="$1" # e.g. "muscles=4" or "category=11" or "equipment=3"
curl -s "https://wger.de/api/v2/exercise/?${FILTER}&language=2&status=2&limit=20&format=json" \
| python -c "
import json,sys
data=json.load(sys.stdin)
print(f'Found {data.get(\"count\",0)} exercises.')
for ex in data.get('results',[]):
print(f\" ID {ex['id']:>4} | muscles: {ex.get('muscles',[])} | equipment: {ex.get('equipment',[])}\")
"
Uses USDA_API_KEY env var if set, otherwise falls back to DEMO_KEY.
DEMO_KEY = 30 requests/hour. Free signup key = 1,000 requests/hour.
# Search foods by name
FOOD="$1"
API_KEY="${USDA_API_KEY:-DEMO_KEY}"
ENCODED=$(python -c "import urllib.parse,sys; print(urllib.parse.quote(sys.argv[1]))" "$FOOD")
curl -s "https://api.nal.usda.gov/fdc/v1/foods/search?api_key=${API_KEY}&query=${ENCODED}&pageSize=5&dataType=Foundation,SR%20Legacy" \
| python -c "
import json,sys
data=json.load(sys.stdin)
foods=data.get('foods',[])
if not foods: print('No foods found.'); sys.exit()
for f in foods:
n={x['nutrientName']:x.get('value','?') for x in f.get('foodNutrients',[])}
cal=n.get('Energy','?'); prot=n.get('Protein','?')
fat=n.get('Total lipid (fat)','?'); carb=n.get('Carbohydrate, by difference','?')
print(f\"{f.get('description','N/A')}\")
print(f\" Per 100g: {cal} kcal | {prot}g protein | {fat}g fat | {carb}g carbs\")
print(f\" FDC ID: {f.get('fdcId','N/A')}\")
print()
"
# Detailed nutrient profile by FDC ID
FDC_ID="$1"
API_KEY="${USDA_API_KEY:-DEMO_KEY}"
curl -s "https://api.nal.usda.gov/fdc/v1/food/${FDC_ID}?api_key=${API_KEY}" \
| python -c "
import json,sys
d=json.load(sys.stdin)
print(f\"Food: {d.get('description','N/A')}\")
print(f\"{'Nutrient':<40} {'Amount':>8} {'Unit'}\")
print('-'*56)
for x in sorted(d.get('foodNutrients',[]),key=lambda x:x.get('nutrient',{}).get('rank',9999)):
nut=x.get('nutrient',{}); amt=x.get('amount',0)
if amt and float(amt)>0:
print(f\" {nut.get('name',''):<38} {amt:>8} {nut.get('unitName','')}\")
"
Use the helper scripts in scripts/ for batch operations,
or run inline for single calculations:
python scripts/body_calc.py bmi <weight_kg> <height_cm>python scripts/body_calc.py tdee <weight_kg> <height_cm> <age> <M|F> <activity 1-5>python scripts/body_calc.py 1rm <weight> <reps>python scripts/body_calc.py macros <tdee_kcal> <cut|maintain|bulk>python scripts/body_calc.py bodyfat <M|F> <neck_cm> <waist_cm> [hip_cm] <height_cm>See references/FORMULAS.md for the science behind each formula.
language=2 for Englishstatus=2 to only get approved exercisesDEMO_KEY has 30 req/hour — add sleep 2 between batch requests or get a free keyexercise/search endpoint uses term not query as the parameter nameAfter running exercise search: confirm results include exercise names, muscle groups, and equipment. After nutrition lookup: confirm per-100g macros are returned with kcal, protein, fat, carbs. After calculators: sanity-check outputs (e.g. TDEE should be 1500-3500 for most adults).
| Task | Source | Endpoint |
|---|---|---|
| Search exercises by name | wger | GET /api/v2/exercise/search/?term=&language=english |
| Exercise details | wger | GET /api/v2/exerciseinfo/{id}/ |
| Filter by muscle | wger | GET /api/v2/exercise/?muscles={id}&language=2&status=2 |
| Filter by equipment | wger | GET /api/v2/exercise/?equipment={id}&language=2&status=2 |
| List categories | wger | GET /api/v2/exercisecategory/ |
| List muscles | wger | GET /api/v2/muscle/ |
| Search foods | USDA | GET /fdc/v1/foods/search?query=&dataType=Foundation,SR Legacy |
| Food details | USDA | GET /fdc/v1/food/{fdcId} |
| BMI / TDEE / 1RM / macros | offline | python scripts/body_calc.py |