Coach
felixrieseberg/claude-coach
Create personalized triathlon, marathon, and ultra-endurance training plans.
Workout planning, macros, and body metrics via wger/USDA. An agent skill from Luciole-Studio/Misaka-Agent.
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutrition --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .claude/skills/fitness-nutrition && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .claude/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutritionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutrition --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .agents/skills/fitness-nutrition && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .agents/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutrition --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .cursor/skills/fitness-nutrition && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .cursor/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Luciole-Studio/Misaka-Agent.git --path misaka/core/skills/assets/optional/health/fitness-nutrition--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutrition --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .gemini/skills/fitness-nutrition && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .gemini/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutritionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .github/skills/fitness-nutrition && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .github/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Luciole-Studio/Misaka-Agent fitness-nutrition --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/misaka/core/skills/assets/optional/health/fitness-nutrition .opencode/skills/fitness-nutrition && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fitness-nutrition" agent skill from https://github.com/Luciole-Studio/Misaka-Agent/tree/main/misaka/core/skills/assets/optional/health/fitness-nutrition into .opencode/skills/fitness-nutrition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fitness-nutrition", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
fitness-nutritionWorkout planning, macros, and body metrics via wger/USDA. An agent skill from Luciole-Studio/Misaka-Agent.
Fitness Nutrition is an agent skill from Luciole-Studio/Misaka-Agent. Workout planning, macros, and body metrics via wger/USDA.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/FORMULAS.md`, `scripts/body_calc.py` and `scripts/nutrition_search.py`).
It sits in Productivity & Automation, covering Health and fitness tracking. The repository describes itself as: A multi-agent research system for the humanities and social sciences. The licence is MIT.
Read from SKILL.md and the folder at commit 3bcf7a3. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythoncurlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
wger.deapi.nal.usda.govFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
DEMO_KEYUSDA_API_KEYAPI_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Fitness Nutrition loads about 2.4k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 19 tokens; SKILL.md has 577 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from Luciole-Studio/Misaka-Agent at commit 3bcf7a3, republished under its MIT licence (© Luciole-Studio). 577 words, ~2,446 tokens.
.claude/skills/fitness-nutrition/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.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 |
© Luciole-Studio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in misaka/core/skills/assets/optional/health/fitness-nutrition of Luciole-Studio/Misaka-Agent.
Open the folder on GitHubat commit 3bcf7a3
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Luciole-Studio/Misaka-Agent, which our catalogue first saw on October 7, 2026.
Fitness Nutrition next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fitness Nutrition this skillLuciole-Studio/Misaka-Agent | 171 | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Coachfelixrieseberg/claude-coach | 199 | 1 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Fitness Analyzerhuifer/WellAlly-health | 960 | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Master Ajahn Chahxr843/Master-skill | 447 | 1 repos | ~2k | Automated safety check: Pass | CC-BY-NC-SA-4.0 | |
| Mental Health Analyzerhuifer/WellAlly-health | 960 | 5 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Nutrition Analyzerhuifer/WellAlly-health | 960 | 5 repos | ~3.3k | Automated safety check: Pass | MIT |
felixrieseberg/claude-coach
Create personalized triathlon, marathon, and ultra-endurance training plans.
huifer/WellAlly-health
分析运动数据、识别运动模式、评估健身进展,并提供个性化训练建议。支持与慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.
xr843/Master-skill
A skill your agent uses when user asks about 南传佛教, 上座部, Theravada, 巴利经典, 正念 sati, 放下, 三法印, 四念处, 出入息念 anapanasati, 戒定慧, 毗婆舍那, 森林禅林派, 巴蓬寺, 阿姜查, 杜多行, 中道, or wants teaching in 阿姜查 Ajahn Chah's voice.
huifer/WellAlly-health
分析心理健康数据、识别心理模式、评估心理健康状况、提供个性化心理健康建议。支持与睡眠、运动、营养等其他健康数据的关联分析。
huifer/WellAlly-health
分析营养数据、识别营养模式、评估营养状况,并提供个性化营养建议。支持与运动、睡眠、慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.
Google-Health-API/google-health-cli
Query Google Health API v4 — steps, heart rate, exercise, sleep, weight, SpO2, HRV, ECG, blood glucose, nutrition, and 40 total data types
Luciole-Studio/Misaka-Agent
Plan and run multi-agent video production pipelines. An agent skill from Luciole-Studio/Misaka-Agent.
Luciole-Studio/Misaka-Agent
AST-aware structural code search and rewrite via ast-grep. An agent skill from Luciole-Studio/Misaka-Agent.
Luciole-Studio/Misaka-Agent
Drug discovery: ChEMBL search, drug-likeness, interactions. An agent skill from Luciole-Studio/Misaka-Agent.
Luciole-Studio/Misaka-Agent
Render MP4/WebM videos from HTML compositions. An agent skill from Luciole-Studio/Misaka-Agent.
Luciole-Studio/Misaka-Agent
Follow the money via public records and sanctions data. An agent skill from Luciole-Studio/Misaka-Agent.
Luciole-Studio/Misaka-Agent
Deploy a Worker live, no account, via wrangler --temporary. An agent skill from Luciole-Studio/Misaka-Agent.
Categories
Workout planning, macros, and body metrics via wger/USDA. An agent skill from Luciole-Studio/Misaka-Agent. Fitness Nutrition is an agent skill from Luciole-Studio/Misaka-Agent. Workout planning, macros, and body metrics via wger/USDA.
Fitness Nutrition fits situations like: tasks that involve Health and fitness tracking.
Run `npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a claude-code`. Or copy the skill folder (misaka/core/skills/assets/optional/health/fitness-nutrition in Luciole-Studio/Misaka-Agent) into .claude/skills/fitness-nutrition in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a codex`. Or copy the skill folder (misaka/core/skills/assets/optional/health/fitness-nutrition in Luciole-Studio/Misaka-Agent) into .agents/skills/fitness-nutrition in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Luciole-Studio/Misaka-Agent --skill fitness-nutrition -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fitness-nutrition, .gemini/skills/fitness-nutrition, .github/skills/fitness-nutrition and .opencode/skills/fitness-nutrition in your project.
Going by SKILL.md and its folder, Fitness Nutrition needs Python for the scripts in its folder, the command-line tools its instructions call (python and curl) and credentials named DEMO_KEY, USDA_API_KEY and API_KEY. Our summary lists: Python 3; A credential in USDA_API_KEY; A credential in DEMO_KEY.
SKILL.md names 2 domains. In commands or code: wger.de and api.nal.usda.gov; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Fitness Nutrition is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 809 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Fitness Nutrition: Coach (felixrieseberg/claude-coach, 199 stars), Fitness Analyzer (huifer/WellAlly-health, 960 stars), Master Ajahn Chah (xr843/Master-skill, 447 stars) and Mental Health Analyzer (huifer/WellAlly-health, 960 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Luciole-Studio (a GitHub organization) maintains it in Luciole-Studio/Misaka-Agent, which has 171 GitHub stars. The repository holds 77 skills in this directory. The repository was last updated on October 8, 2026.
Source: Luciole-Studio/Misaka-Agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.