Personal Athlete 81 Grid

SkillAI & models

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.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Personal Athlete 81 Grid skill

What this skill tells your AI

The instructions your AI receives, as published by twhsi/skills in skills/personal-athlete-81-grid/SKILL.md and read by ahel’s review.

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:

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:

{
  "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:

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:

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:

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.

Signals

GitHub stars
259
Forks
38
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
personal-athlete-81-grid
Source
github.com/twhsi/skills