/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
$ npx -y skills add twhsi/skills --skill personal-athlete-81-grid --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/personal-athlete-81-grid
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
personal-athlete-81-grid.SKILL.mdname: personal-athlete-81-grid
description: 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.
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:
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:
| Layer | Default color | Meaning | |---|---|---| | Center goal | red `#ff260f` | final target, identity-level athletic goal | | Domain cells | pink `#fb8aa0` | the eight main domains and outer domain centers | | Hard skills | white `#ffffff` | sport technique, body mechanics, concrete drills | | Mental/social/long-term | cyan `#65eadb` | psychology, character, recovery, relationships, longevity | | Section lines | black `#050505` | 3x3 blocks | | Cell lines | gray `#b9b9b9` | individual 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.
Read more
name: personal-athlete-81-grid description: 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.
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:
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:
| Layer | Default color | Meaning | |---|---|---| | Center goal | red `#ff260f` | final target, identity-level athletic goal | | Domain cells | pink `#fb8aa0` | the eight main domains and outer domain centers | | Hard skills | white `#ffffff` | sport technique, body mechanics, concrete drills | | Mental/social/long-term | cyan `#65eadb` | psychology, character, recovery, relationships, longevity | | Section lines | black `#050505` | 3x3 blocks | | Cell lines | gray `#b9b9b9` | individual 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.
Three Kings 2.2: compress with iMandalArt, address with BIRD, and publish with an A4 eight-page booklet. iMandalArt, FIRE semantic analysis, planning, and publishing workflows for Claude Code, Codex, and mainstream LLM agents.
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