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Agent Skill · 研究检索

fit(适合)

fit 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

fit 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为权限未标注;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,899。

总安装 9,008周安装 383GitHub Stars 公开资料未说明下载 3,156核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:fit(适合)
来源仓库:https://github.com/agimodel/fit
安装命令:
openclaw skills install fit
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 fit

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

fit 作为个人健身操作系统,诊断身体实际需求。动态调整训练计划以适应个体生理变化。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。超越固定锻炼表,强调系统适应性匹配。安装命令:openclaw skills install fit。健康建议不能替代专业医师诊断。

fit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install fit;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

fit 怎么安装?

在终端执行 openclaw skills install fit。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

fit 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

fit 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

fit 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

fit 用的人多吗?

公开数据是累计安装 9,008 次,近一周安装 383 次,下载 3,156 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

fit 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
fit

适合 · 本页

9,008—权限未标注MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
fit
description
>

Fit

What Most Fitness Advice Gets Wrong

Fitness advice is almost always written for someone with unlimited time, perfect recovery, consistent sleep, no stress, no travel, and a body that responds predictably to training.

That person does not exist.

The people who actually get fit — who look different, move differently, and feel different a year from now than they do today — are not the ones who followed the perfect program. They are the ones who followed a good-enough program consistently for long enough that consistency compounded into transformation.

This skill is built for real people with real constraints.


The System

FITNESS_OS = {
  "assessment": {
    "current_state": ["Current weight and body composition if known",
                      "Current training frequency and type",
                      "Movement limitations or injuries",
                      "Energy levels across the day",
                      "Sleep quality and quantity"],
    "goal_clarity":  {
      "aesthetic":     "Body composition change — fat loss, muscle gain, or both",
      "performance":   "Specific metric — run 5K, deadlift bodyweight, 10 pullups",
      "health":        "Blood markers, blood pressure, longevity, pain reduction",
      "functional":    "Move better, carry more, hurt less"
    },
    "constraint_map": ["Days per week available for training",
                       "Minutes per session realistic",
                       "Equipment available",
                       "Injuries or restrictions",
                       "Travel frequency"]
  }
}

Training Architecture

PROGRAM_DESIGN = {
  "minimum_effective_dose": {
    "principle": "The smallest training stimulus that produces the desired adaptation.
                  More is not better. Enough is better.",
    "research":  "2x per week per muscle group produces ~80% of the gains of 4x per week.
                  3x per week per muscle group captures nearly all available adaptation.",
    "implication": "A 3-day full-body program done consistently beats a 6-day program
                    done sporadically for the vast majority of non-competitive athletes."
  },

  "progressive_overload": {
    "definition": "Systematically increasing training stimulus over time to force adaptation",
    "methods":    ["Add weight to the bar",
                   "Add reps at same weight",
                   "Add sets",
                   "Reduce rest period",
                   "Improve movement quality"],
    "tracking":   """
      def log_workout(exercise, sets, reps, weight):
          session = {
              "date": today,
              "exercise": exercise,
              "volume": sets * reps * weight,
              "top_set": max_weight_lifted
          }
          compare_to_last_session(session)
          if no_progress_in_3_weeks:
              flag_for_program_adjustment()
    """
  },

  "recovery_management": {
    "signals_of_under_recovery": ["Resting HR elevated vs baseline",
                                   "Performance declining week over week",
                                   "Motivation to train is unusually low",
                                   "Sleep quality deteriorating",
                                   "Persistent muscle soreness beyond 72 hours"],
    "response":  "Reduce volume by 40-50% for one week before resuming progression"
  }
}

Nutrition for Fitness Goals

NUTRITION_FRAMEWORK = {
  "fat_loss": {
    "principle":  "Caloric deficit is required. Protein is non-negotiable.",
    "target":     "0.7-1g protein per lb bodyweight preserves muscle during deficit",
    "deficit":    "250-500 calories below maintenance — aggressive enough to progress,
                   conservative enough to preserve muscle and sustain adherence",
    "rate":       "0.5-1% of bodyweight per week is sustainable fat loss"
  },
  "muscle_gain": {
    "principle":  "Caloric surplus + adequate protein + progressive overload",
    "target":     "0.7-1g protein per lb bodyweight",
    "surplus":    "200-300 calories above maintenance — minimize fat gain",
    "rate":       "0.25-0.5 lb per week for natural trainers is realistic muscle gain"
  },
  "body_recomposition": {
    "who":        "Beginners, detrained individuals, people returning from injury",
    "approach":   "Maintenance calories, high protein, progressive training",
    "reality":    "Simultaneous fat loss and muscle gain is possible but slower than
                   dedicated phases for either goal"
  }
}

When Life Disrupts the Plan

DISRUPTION_PROTOCOLS = {
  "travel": {
    "hotel_gym":     "Minimum: 30 min, compound movements, maintain frequency",
    "no_gym":        "Bodyweight protocol — push, pull, hinge, squat, carry variations",
    "principle":     "Maintenance beats nothing. One session per week prevents detraining."
  },
  "injury": {
    "train_around":  "Almost every injury allows training something — find what is possible",
    "upper_body":    "Leg day continues. Lower body injury is not a rest day.",
    "return":        "Return at 60% intensity, progress over 2-3 weeks back to full load"
  },
  "missed_weeks": {
    "rule":          "Never miss twice. One disruption is life. Two is a pattern.",
    "return":        "Reduce weight by 20-30%, rebuild over 1-2 weeks — prevents injury"
  }
}

Progress Tracking

METRICS_THAT_MATTER = {
  "performance":    "Weight lifted, reps completed, pace, distance — objective and motivating",
  "body":           "Weekly average weight, monthly measurements, photos every 4 weeks",
  "habits":         "Training sessions completed vs planned — consistency is the metric",
  "energy":         "Subjective energy and mood — leading indicator of program sustainability",
  "avoid":          "Daily scale weight as primary metric — noise overwhelms signal"
}

Quality Check

  • [ ] Goal is specific and time-bound
  • [ ] Program is matched to actual available time and equipment
  • [ ] Progressive overload built into the plan
  • [ ] Nutrition targets provided for stated goal
  • [ ] Disruption protocols ready for travel and injury
  • [ ] Progress tracking is objective and scheduled

平台分布

OpenClaw

78.03%
按下载量换算2,463

安全审计

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权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。目前只有一个公开来源,建议同时核对源仓库。

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