dorodango
Polishes working code through successive quality passes in fresh subagents. Use after tests pass when code needs multi-dimension refinement before r…
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技能内容
Dorodango Polishing Workflow
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.
When To Use
- After initial implementation is complete and tests
pass
- Code works but needs refinement across multiple
quality dimensions
- Preparing code for review or release
- Resuming a previous polishing session
When NOT To Use
- Code does not compile or pass basic tests (fix first)
- Single-dimension improvement needed (use the specific
skill directly: pensive:code-refinement, etc.)
- Greenfield design phase (use brainstorming instead)
Pass Sequence
Four quality dimensions, each a self-contained pass:
- Correctness - run tests, fix failures
- Clarity - code readability and structure
- Consistency - naming, patterns, style alignment
- Polish - documentation, error messages, edges
See modules/pass-definitions.md for detailed scope
of each pass type.
Convergence Model
- Each pass targets one dimension
- A pass that finds
issues_found: 0marks that
dimension as converged
- Convergence is irreversible per run; a converged
dimension is not re-run
- When all 4 dimensions converge, polishing is complete
- Maximum 10 total passes (hard limit)
- If not converged after 10 passes, surface state to
human with recommendation to split into smaller units
State Persistence
State 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.
Subagent Isolation
Each pass dispatches a self-contained subagent to
prevent context accumulation. The subagent receives:
- Target directory/files
- Pass type and scope (from pass-definitions module)
- Previous pass results (summary only, not full context)
Subagent dispatch is optional for targets under 100
lines of code; in-session review is sufficient for
small files.
Workflow
- Initialize state file (or load existing)
- Determine next unconverged dimension
- Dispatch subagent for that dimension
- Record results in state file
- If dimension converged (0 issues), mark it
- If all dimensions converged or 10 passes reached,
stop
- Otherwise, proceed to next dimension
Cross-References
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
Exit Criteria
- [ ]
.attune/dorodango-state.jsonexists with"converged": trueand all four dimensions
(correctness, clarity, consistency, polish) listed under converged_dimensions.
- [ ] Total
pass_countin 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.
- [ ] The correctness dimension converges only after all tests pass (exit code 0); a
correctness pass that finds failing tests never marks the dimension as converged.
- [ ] Each pass is dispatched as a separate subagent for targets over 100 lines, confirmed by
the state file recording individual pass results rather than a single bulk entry.
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