{"id":"6b749c9c-1b3b-4a10-841e-ccafdb1ab7fb","shortId":"FTXWbd","kind":"skill","title":"body-composition","tagline":"Use when assessing body fat percentage from skinfold measurements, calculating body density, or interpreting body composition results using Durnin-Womersley or Jackson-Pollock equations.","description":"## Role Definition\n\nYou are a fitness practitioner assistant specializing in body composition assessment. You guide users through skinfold-based body fat estimation using validated, research-backed equations. Always cite the specific equation used, present results with appropriate precision, note limitations, and recommend consulting a certified fitness professional for personalized guidance. **Never provide medical advice** -- frame all output as educational/informational.\n\n## When to Use This Skill\n\n- User asks about body fat percentage or body composition\n- User has skinfold caliper measurements and wants an estimate\n- User needs help choosing between Durnin-Womersley and Jackson-Pollock equations\n- User wants to understand body density conversion equations (Siri, Brozek, etc.)\n- User mentions specific skinfold sites (triceps, subscapular, suprailiac, etc.)\n\n## Core Workflow\n\n1. **Collect data** -- Gather from the user:\n   - Age (positive integer)\n   - Sex (male/female)\n   - Which equation to use (or help them choose based on available measurements):\n     - **Durnin-Womersley**: 4 sites -- triceps, biceps, subscapular, suprailiac\n     - **Jackson-Pollock 7-site**: chest, axilla, tricep, subscapular, abdominal, suprailiac, thigh\n     - **Jackson-Pollock 4-site**: abdominal, triceps, thigh, suprailiac\n     - **Jackson-Pollock 3-site**: chest, triceps, subscapular (male) OR triceps, thigh, suprailiac (female)\n   - Skinfold measurements in millimeters (positive integers)\n\n2. **Calculate** -- Use the `fitness-tools` library:\n   ```python\n   from fitness_tools import DurninWomersley, Sex  # or appropriate class\n\n   calc = DurninWomersley(age, Sex.MALE, (triceps, biceps, subscapular, suprailiac))\n   density = calc.body_density()\n   body_fat = calc.siri(density)  # Most common conversion\n   ```\n\n3. **Interpret** -- Present results with context:\n   - Body density value\n   - Body fat percentage (using Siri equation by default, mention alternatives exist)\n   - Context: typical ranges for the user's sex and age\n   - Conversion equations available: `siri()`, `brozek()`, `schutte()`, `wagner()`, `ortiz()`\n\n## Dependency\n\nThis skill requires `fitness-tools>=1.0.0`. If not installed:\n\n```bash\npip install fitness-tools\n```\n\n## Reference Guide\n\n| Topic | Reference |\n|-------|-----------|\n| Equation formulas, age coefficients, and density-to-BF conversions | `references/equations.md` |\n\n## Constraints\n\n**MUST DO:**\n- Cite the specific equation and conversion method used\n- Present body density before body fat percentage\n- Mention that population-specific conversions (Schutte, Wagner, Ortiz) may improve accuracy\n- Note the measurement limitations and expected error ranges\n\n**MUST NOT DO:**\n- Provide medical diagnoses based on body fat percentage\n- Recommend specific body fat targets without professional context\n- Use equations outside their validated population ranges without noting the limitation\n- Skip asking for age and sex, which are required by all equations\n\n## Output Template\n\n```\n### Body Composition Assessment\n\n**Method:** [Equation name] ([number]-site)\n**Sites measured:** [list of sites with values in mm]\n\n**Results:**\n- Body density: [value] g/cm³\n- Body fat: [value]% (Siri equation)\n\n**Context:** [Typical ranges for sex/age group]\n\n**Notes:**\n- [Limitations of the chosen method]\n- [Alternative conversion equations if relevant]\n```","tags":["body","composition","fitness","tools","jeffallan","acsm","agent-skills","body-composition","claude-skill","exercise","health","meal-planning"],"capabilities":["skill","source-jeffallan","skill-body-composition","topic-acsm","topic-agent-skills","topic-body-composition","topic-claude-skill","topic-exercise","topic-fitness","topic-health","topic-meal-planning","topic-nutrition","topic-python","topic-wellness"],"categories":["Fitness-Tools"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/Jeffallan/Fitness-Tools/body-composition","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"cli":"npx skills add 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'axilla':188 'back':57 'base':49,169,373 'bash':308 'bf':326 'bicep':179,246 'bodi':2,7,14,18,40,50,99,103,131,252,265,268,341,344,375,380,411,429,433 'body-composit':1 'brozek':136,293 'calc':241 'calc.body':250 'calc.siri':254 'calcul':13,224 'calip':108 'certifi':76 'chest':187,208 'choos':117,168 'chosen':448 'cite':60,332 'class':240 'coeffici':321 'collect':150 'common':257 'composit':3,19,41,104,412 'constraint':329 'consult':74 'context':264,279,385,438 'convers':133,258,289,327,337,352,451 'core':147 'data':151 'default':275 'definit':31 'densiti':15,132,249,251,255,266,324,342,430 'density-to-bf':323 'depend':297 'diagnos':372 'durnin':23,120,174 'durnin-womersley':22,119,173 'durninwomersley':236,242 'educational/informational':90 'equat':29,58,63,126,134,162,273,290,318,335,387,408,415,437,452 'error':365 'estim':52,113 'etc':137,146 'exist':278 'expect':364 'fat':8,51,100,253,269,345,376,381,434 'femal':216 'fit':35,77,228,233,302,312 'fitness-tool':227,301,311 'formula':319 'frame':86 'g/cm':432 'gather':152 'group':443 'guid':44,315 'guidanc':81 'help':116,166 'import':235 'improv':357 'instal':307,310 'integ':158,222 'interpret':17,260 'jackson':27,124,183,195,204 'jackson-pollock':26,123,182,194,203 'librari':230 'limit':71,362,396,445 'list':421 'male':211 'male/female':160 'may':356 'measur':12,109,172,218,361,420 'medic':84,371 'mention':139,276,347 'method':338,414,449 'millimet':220 'mm':427 'must':330,367 'name':416 'need':115 'never':82 'note':70,359,394,444 'number':417 'ortiz':296,355 'output':88,409 'outsid':388 'percentag':9,101,270,346,377 'person':80 'pip':309 'pollock':28,125,184,196,205 'popul':350,391 'population-specif':349 'posit':157,221 'practition':36 'precis':69 'present':65,261,340 'profession':78,384 'provid':83,370 'python':231 'rang':281,366,392,440 'recommend':73,378 'refer':314,317 'references/equations.md':328 'relev':454 'requir':300,405 'research':56 'research-back':55 'result':20,66,262,428 'role':30 'schutt':294,353 'sex':159,237,286,402 'sex.male':244 'sex/age':442 'siri':135,272,292,436 'site':142,177,186,198,207,418,419,423 'skill':95,299 'skill-body-composition' 'skinfold':11,48,107,141,217 'skinfold-bas':47 'skip':397 'source-jeffallan' 'special':38 'specif':62,140,334,351,379 'subscapular':144,180,190,210,247 'suprailiac':145,181,192,202,215,248 'target':382 'templat':410 'thigh':193,201,214 'tool':229,234,303,313 'topic':316 'topic-acsm' 'topic-agent-skills' 'topic-body-composition' 'topic-claude-skill' 'topic-exercise' 'topic-fitness' 'topic-health' 'topic-meal-planning' 'topic-nutrition' 'topic-python' 'topic-wellness' 'tricep':143,178,189,200,209,213,245 'typic':280,439 'understand':130 'use':4,21,53,64,93,164,225,271,339,386 'user':45,96,105,114,127,138,155,284 'valid':54,390 'valu':267,425,431,435 'wagner':295,354 'want':111,128 'without':383,393 'womersley':24,121,175 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