Personal Athlete 81 Grid logo

Personal Athlete 81 Grid

Community
twhsi
personal-athlete-81-grid

Create a personal athlete 81-cell MandalArt grid from an Ohtani Shohei-style 64+8+1 model. Use when the user asks for 大谷翔平 81 宮格, 個人運動員81宮格, sports skill maps, athlete training Mandala charts, badminton 81 grids, or editable JSON/SVG/PNG-ready athlete development templates with Ohtani-style colors.

Overview

Publishertwhsi
Repositoryskills
Skill namepersonal-athlete-81-grid
Stars
259
Forks
37
Bundled files
5
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by twhsi on GitHub. Read the source before you install it.

Installation

Install the Personal Athlete 81 Grid AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/twhsi/skills/tree/main/skills/personal-athlete-81-grid
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/twhsi/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/personal-athlete-81-grid .claude/skills/personal-athlete-81-grid
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Personal Athlete 81 Grid in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Personal Athlete 81 Grid on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Personal Athlete 81 Grid is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Personal Athlete 81 Grid

Purpose

Turn an athlete's core goal into a square 9x9 MandalArt grid:

  • 1 center goal: the athlete's north star.
  • 8 domains: the center 3x3 ring around the goal.
  • 64 extension cells: each domain expands into eight concrete actions.

Default visual style is the Ohtani Shohei reference: thick black 3x3 section lines, short bold text, red center, pink domain centers/core layer, white hard skills, cyan mental/social/recovery/long-term layer.

Workflow

  1. Identify the athlete, sport, and center goal.
  2. Choose eight domains. Prefer 5 hard or sport-skill domains and 3 long-term domains.
  3. Expand each domain into eight short, editable action cells.
  4. Save as JSON first. JSON is the source of truth; SVG/PNG are outputs.
  5. Render a square 81-cell visual if requested.

For badminton, a good default domain set is:

text
後場攻防、切吊變化、網前手感、重心步法、發接前三、恢復保養、球友情場、長壽榜樣

JSON Schema

Use this compact shape:

json
{
  "title": "永錫羽毛球81宮格",
  "center": "越老越健康\n越久越快樂\n重心強",
  "visual_style": "ohtani",
  "domains": [
    {
      "name": "後場攻防",
      "type": "hard_skill",
      "items": ["側身準備", "高遠拉開", "殺球角度", "一殺一抽", "抽球拍面", "殺後銜接", "切吊變化", "教練回饋"]
    }
  ]
}

Rules:

  • Exactly eight domains.
  • Each domain has exactly eight items.
  • Keep each label short enough for a square cell, usually 2-6 Chinese characters.
  • Do not duplicate the domain name in items; the renderer places it in each outer 3x3 center.
  • Use line breaks in center only when needed.

Ohtani Visual Color Rules

Use these colors unless the user asks for another palette:

LayerDefault colorMeaning
Center goalred #ff260ffinal target, identity-level athletic goal
Domain cellspink #fb8aa0the eight main domains and outer domain centers
Hard skillswhite #ffffffsport technique, body mechanics, concrete drills
Mental/social/long-termcyan #65eadbpsychology, character, recovery, relationships, longevity
Section linesblack #0505053x3 blocks
Cell linesgray #b9b9b9individual cells

Map domain types:

  • hard_skill: white outer cells, pink domain center.
  • body: white outer cells, pink domain center.
  • recovery: cyan outer cells, pink domain center.
  • mental: cyan outer cells, pink domain center.
  • social: cyan outer cells, pink domain center.
  • longevity: cyan outer cells, pink domain center.

Rendering

Use the bundled script when a deterministic SVG is useful:

bash
python3 scripts/render_ohtani_81_grid.py assets/yongxi-badminton.json output.svg

Then convert SVG to PNG with a local tool if available, such as:

bash
qlmanage -t -s 2400 -o . output.svg

The script expects the JSON schema above and outputs a square 2400x2400 SVG.

Prompt Pattern

When the user gives only a sport and goal, use this pattern internally:

text
Create an Ohtani-style personal athlete 81 grid for SPORT.
Center goal: GOAL.
Return 8 domains, each with 8 short action cells.
Use 5 sport-skill/body domains and 3 recovery/mental/social/longevity domains.
Keep labels concise enough for a square 9x9 grid.
Use JSON as the editable source.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Personal Athlete 81 Grid AI skill do?

Create a personal athlete 81-cell MandalArt grid from an Ohtani Shohei-style 64+8+1 model. Use when the user asks for 大谷翔平 81 宮格, 個人運動員81宮格, sports skill maps, athlete training Mandala charts, badminton 81 grids, or editable JSON/SVG/PNG-ready athlete development templates with Ohtani-style colors.

Why use Personal Athlete 81 Grid on TypingMind?

Because you install it once and use it with any model. Personal Athlete 81 Grid is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Personal Athlete 81 Grid in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/twhsi/skills/tree/main/skills/personal-athlete-81-grid. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Personal Athlete 81 Grid?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Personal Athlete 81 Grid?

As many as you like. As long as a model supports skills, you can use Personal Athlete 81 Grid with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Personal Athlete 81 Grid AI skill free?

It is published on GitHub by twhsi. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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