plugins/attune/skills/dorodango/SKILL.md
Polishes working code through successive quality passes in fresh subagents. Use after tests pass when code needs multi-dimension refinement before release.
npx skillsauth add athola/claude-night-market dorodangoInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Named after the Japanese art of polishing a ball of dirt into a high-gloss sphere. Applied to code: take the initial implementation (the "mud ball") and refine it through successive quality passes until it shines.
Four quality dimensions, each a self-contained pass:
See modules/pass-definitions.md for detailed scope
of each pass type.
issues_found: 0 marks that
dimension as convergedState tracked in .attune/dorodango-state.json:
{
"target": "plugins/foo",
"started_at": "2026-03-18T12:00:00Z",
"pass_count": 3,
"passes": [
{
"type": "correctness",
"issues_found": 2,
"issues_fixed": 2
},
{
"type": "clarity",
"issues_found": 5,
"issues_fixed": 5
},
{
"type": "consistency",
"issues_found": 0
}
],
"converged_dimensions": ["consistency"],
"converged": false
}
This file enables resume across sessions. On resume, skip converged dimensions and continue from the next unconverged dimension.
Each pass dispatches a self-contained subagent to prevent context accumulation. The subagent receives:
Subagent dispatch is optional for targets under 100 lines of code; in-session review is sufficient for small files.
pensive:code-refinement - used in clarity passconserve:code-quality-principles - KISS/YAGNI/SOLIDimbue:latent-space-engineering - frame pass prompts
with emotional framing for better results.attune/dorodango-state.json exists with "converged": true and all four dimensions
(correctness, clarity, consistency, polish) listed under converged_dimensions.pass_count in the state file is <= 10; if 10 passes complete without full
convergence, the skill surfaces the unconverged dimensions to the user with a recommendation
to split the target into smaller units.data-ai
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development
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