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Get Started Free →twhsi/personal-athlete-81-grid
Create a personal athlete 81-cell MandalArt grid from an Ohtani Shohei-style 64+8+1 model.
Passed 23 of 24 test cases with the skill, and 10 of 24 without it.
and 20 more in the full report
14 fixed10 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
What exact macOS CLI utility command is recommended in the workflow to render the generated output.svg into a PNG image file in the current directory?
| Checked | Without skill | With skill |
|---|---|---|
| The command executes the qlmanage utility with parameters -t -s 2400 -o . output.svg. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
5 hard or sport-skill domains and 3 long-term domains.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
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"]
test cases passed, vs 10 / 24 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.