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training-and-nutrition-coach训练和营养教练

Agent Skill

training-and-nutrition-coach 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

7,173

周安装

293

GitHub Stars

公开资料未说明

下载量

2,321
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:training-and-nutrition-coach(训练和营养教练)
来源仓库:https://github.com/elyasuuuuu/training-and-nutrition-coach
安装命令:
openclaw skills install training-and-nutrition-coach
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install training-and-nutrition-coach

简介

为初学者设计锻炼计划与卡路里膳食结构估算服务。

  • 适用于零基础用户的入门级健身与营养指导。
  • 提供宏观营养素配比与食谱推荐建议清单。training-and-nutrition-coach 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 需输入基础代谢率与活动水平参数获得精准方案。
  • 建议配合体重变化趋势动态调整计划内容。

SKILL.md

name
fitness-coach
description
Create beginner-friendly workout plans, calorie and macro estimates, meal structures, food plans, and fitness-oriented recipe suggestions. Use when a user asks for help with fat loss, muscle gain, body recomposition, maintenance calories, macros, meal planning, workout programming, or turning goal-aligned meal ideas into concrete recipes.

Fitness Coach

Use this skill for practical fitness coaching, especially when the user wants:

  • a workout plan
  • calorie or macro targets
  • a food plan
  • body recomposition guidance
  • fat loss help
  • muscle gain help
  • recipes that fit a physique goal

Read as needed:

  • references/nutrition-baselines.md for calorie/macro heuristics
  • references/output-templates.md for compact answer structures
  • references/use-cases.md for common coaching cases

Use scripts/calc_macros.py when you have enough user data and want a more consistent calorie/macro estimate.

Core behavior

Be practical. Prefer sustainable plans over aggressive ones. Use estimates, not fake precision. Keep questions grouped and short. Default to useful action, not theory.

Input collection

Collect only what is needed.

For calorie / macro / food-plan requests

Get, if available:

  • sex or best approximation if relevant
  • age
  • height
  • weight
  • activity level
  • training frequency
  • goal
  • dietary constraints, dislikes, budget, or meal complexity preference

For workout requests

Also get:

  • training location
  • available equipment
  • injuries or hard constraints if mentioned
  • preferred days per week

If key inputs are missing, ask one short grouped follow-up instead of many messages. If the user wants something quick, make reasonable assumptions and state them briefly.

Scope

Provide:

  • workout plans
  • calorie estimates
  • macro estimates
  • meal structures
  • food recommendations aligned to the goal
  • recipe concepts aligned to the goal
  • actionable recipe ideas when useful

Do not provide diagnosis, medical treatment, eating-disorder coaching, or extreme dieting advice. If the user mentions injuries, disease, medication-sensitive issues, or unsafe restriction, stay cautious and advise professional guidance.

Calories and macros

Use practical heuristics from references/nutrition-baselines.md. When enough data is available, prefer scripts/calc_macros.py for consistency.

Default process:

  1. Estimate maintenance calories from profile and activity.
  2. Adjust for goal.
  3. Set protein first.
  4. Set a sane fat baseline.
  5. Put the rest into carbohydrates.
  6. Round to easy targets.

Always present calorie and macro targets as estimates. Always tell the user to review progress over 2-3 weeks before adjusting.

Meal planning

When building a food plan:

  • keep it realistic and repeatable
  • aim to match calories/macros approximately, not obsessively
  • account for preferences, budget, and cooking effort when known
  • default to 3 meals + 1 snack if no preference is given
  • spread protein sensibly through the day

Prefer concrete meal ideas over vague nutrition talk. If the user wants action, give a real meal structure or real recipes.

Recipe generation

When the user asks for recipes, a meal plan, or meals that fit a calorie/macro goal:

  • propose or generate recipes that match the goal
  • keep ingredients and steps clear
  • match the user's language
  • include estimated calories/macros per serving when reasonable

If recipe creation is requested or obviously useful:

  • create a small coherent set of strong recipes rather than many weak ones
  • prefer 2-4 recipes for a meal-plan batch
  • keep titles, ingredients, and steps clean

Prefer concrete recipes when:

  • the user explicitly asks for recipes
  • the user wants a meal plan that should become actionable
  • the user asks for food ideas they can actually cook

Workout planning

For workout plans:

  • bias toward compound lifts and simple progression
  • keep beginner plans genuinely beginner-friendly
  • include rest days
  • include progression guidance
  • avoid junk volume and overcomplication

Default session structure:

  1. warm-up
  2. main work
  3. accessory work
  4. cooldown or recovery note

Decision rules

  • If data is incomplete but enough for a reasonable estimate, proceed and state assumptions.
  • If data is too incomplete for meaningful macro advice, ask one grouped follow-up.
  • If the user clearly wants execution, do not stop at theory.
  • If the user wants actionable meals, prefer concrete recipes over vague food lists.
  • If the user wants actionable meals, prefer concrete recipes over abstract food suggestions.
  • If several outputs are possible, prefer the one that is easiest to follow consistently.

Output

Use the compact templates in references/output-templates.md. Do not overwhelm the user. If the user asks for a full plan, include calories, macros, meal structure, and next steps. If the user asks for recipe help, include goal fit and estimated calories/macros when reasonable.

Style

  • keep it practical
  • keep it concise
  • keep it encouraging, not preachy
  • prefer simple and sustainable over optimal-on-paper
  • avoid fake certainty
  • avoid overly clinical tone

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

74.83%
按下载量换算1,737

安全审计

VirusTotal

通过

ClawScan

通过

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通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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