sparky

name	sparky
description	SparkyFitness CLI for food diary, exercise tracking, biometric check-ins, and health summaries.
homepage	https://github.com/CodeWithCJ/SparkyFitness
metadata	{"clawdbot":{"emoji":"🏃","requires":{"bins":"[Truncated]"}}}

sparky

Use sparky to interact with a self-hosted SparkyFitness server — log food, exercise, weight, steps, and mood.

Install

• Homebrew (macOS/Linux): brew tap aronjanosch/tap && brew install sparky-cli
• Build from source (requires Go 1.21+):

  git clone https://github.com/aronjanosch/sparky-cli
  cd sparky-cli
  go build -o sparky .
  sudo mv sparky /usr/local/bin/
  

Setup (once)

• sparky config set-url <url> — e.g. sparky config set-url https://sparky.example.com
• sparky config set-key <key>
• sparky config show
• sparky ping — verify connection

Food

• Search: sparky food search "chicken breast" [-l 10] — local DB first, falls back to Open Food Facts; shows Brand column
• Search by barcode: sparky food search --barcode 4061458284547 — exact product lookup, no ambiguity
• Log by name: sparky food log "chicken breast" -m lunch -q 150 -u g [-d YYYY-MM-DD]
• Log by barcode: sparky food log --barcode 4061458284547 -m lunch -q 113 -u g — most reliable, no brand guessing
• Log by ID: sparky food log --id <uuid> -m lunch -q 150 -u g — skips search, unambiguous
• Pick result: sparky food log "Hähnchenbrust" --pick 2 — select Nth search result instead of defaulting to results[0]
• Diary: sparky food diary [-d YYYY-MM-DD]
• Delete entry: sparky food delete <uuid>
• Remove from library: sparky food remove <external_id> — purge a wrongly imported product from local library

Exercise

• Search: sparky exercise search "bench press" [-l 10] — local DB first, falls back to Free Exercise DB
• Search external only: sparky exercise search --external "pushup" — bypasses local cache
• Log by name: sparky exercise log "Pushups" [--duration 45] [--calories 400] [-d YYYY-MM-DD]
• Log by ID: sparky exercise log --id <uuid> --set 10x80@8 --set 10x80@9 — skips search, unambiguous
• Sets format: REPS[xWEIGHT][@RPE] — e.g. 10x80@8 = 10 reps, 80 kg, RPE 8; 10x80 or 10@8 also valid
• Diary: sparky exercise diary [-d YYYY-MM-DD]
• Delete: sparky exercise delete <uuid>

Check-ins

• Weight: sparky checkin weight 75.5 [-u kg|lbs] [-d YYYY-MM-DD]
• Steps: sparky checkin steps 9500 [-d YYYY-MM-DD]
• Mood: sparky checkin mood 8 [-n "notes"] [-d YYYY-MM-DD]
• Diary: sparky checkin diary [-d YYYY-MM-DD] — shows biometrics + mood together

Summary & trends

• sparky summary [-s YYYY-MM-DD] [-e YYYY-MM-DD] — nutrition/exercise/wellbeing totals (default: last 7 days)
• sparky trends [-n 30] — day-by-day nutrition table

Agentic workflow (always prefer --id to avoid ambiguity)

Exercise — search first, then log by ID:

# 1. Find candidates; use --external to bypass local cache if needed
sparky -j exercise search --external "pushup"
# Each result has is_local: true/false
#   is_local: true  → id is a UUID → use --id directly
#   is_local: false → id is a source string → log by exact name to import first,
#                     then search again to get the UUID

# 2a. Local exercise
sparky -j exercise log --id <uuid> --set 3x10@8

# 2b. External exercise (import on first log, then switch to --id)
sparky -j exercise log "Pushups" --set 3x10
sparky -j exercise search "Pushups"        # now is_local: true
sparky -j exercise log --id <uuid> --set 3x10

Food — preferred agentic workflow:

# Option A: barcode (most reliable)
sparky food log --barcode 4061458284547 -q 113 -u g -m lunch

# Option B: search → inspect brand+macros → log by --id
sparky -j food search "Hähnchenbrust"
# check brand + calories in results; pick the right one
sparky food log --id <uuid> -q 400 -u g -m dinner

# Option C: search with --pick N (when brand column shows the right one)
sparky food log "Hähnchenbrust" --pick 3 -q 400 -u g -m dinner

# Remove a bad import from local library
sparky food remove <external_id>   # external_id from search results

Notes

• -j / --json is a root-level flag: sparky -j food diary, not sparky food diary -j
• Always verify brand in search results before logging — Open Food Facts has many products with identical names
• --barcode is the most reliable option when the product has a scannable barcode
• --pick N selects the Nth result (1-based); exact local match bypasses --pick entirely
• Both search commands fall back to online providers automatically; matches are added to your library on first log
• Weight is stored in kg; lbs are auto-converted (166 lbs → 75.30 kg)
• Full UUIDs for delete: sparky -j food diary | jq '.[0].id'
• Meal options: breakfast, lunch, dinner, snacks (default: snacks)