
Dorodango
- 74 installs
- 325 repo stars
- Updated August 2, 2026
- athola/claude-night-market
Dorodango is an agent skill that defines correctness, clarity, and consistency passes for the dorodango code-polishing workflow.
About
Dorodango (pass-definitions) documents each quality pass in the attune dorodango polishing workflow for solo builders who want agents to improve code in layers instead of one messy refactor. Pass 1 targets correctness with the test suite and edge cases; Pass 2 targets readability without behavior changes; Pass 3 targets project conventions and patterns, optionally using style-gene-transfer when exemplars exist. Each pass states goals, scope, agent prompt focus, tools, and a clear convergence metric. Install it when you orchestrate multi-agent or multi-step polish after features land—especially if you already use the parent dorodango skill and need precise pass boundaries so agents do not scope-creep across correctness and style in one shot.
- Pass 1 Correctness: pytest/runner, fix failures only—convergence 0 test failures
- Pass 2 Clarity: naming, function length, dead code—convergence 0 clarity issues
- Pass 3 Consistency: naming conventions, imports, error/logging patterns vs codebase
- Per-pass agent prompt focus and tool hints (Bash, Edit, Read, style-gene-transfer)
- Child definition skill for attune:dorodango parent workflow
Dorodango by the numbers
- 74 all-time installs (skills.sh)
- Ranked #509 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 74 |
|---|---|
| repo stars | ★ 325 |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 2, 2026 |
| Repository | athola/claude-night-market ↗ |
What it does
Run the dorodango multi-pass polish loop—correctness, clarity, consistency—with defined agent focus and convergence criteria per pass.
Who is it for?
Best when you use pytest-backed repos and want a repeatable polish ritual after implementation, with parent skill attune:dorodango.
Skip if: Greenfield scaffolding with no tests yet, or projects that only need a one-off lint fix without a multi-pass workflow.
When should I use this skill?
Executing or scoping a pass within the parent attune:dorodango polishing workflow.
What you get
You run ordered passes with explicit convergence (0 failures, 0 clarity issues, convention alignment) and scoped agent instructions per pass.
- Pass-scoped polish with stated convergence metric
- Convention-aligned codebase segment after Pass 3
By the numbers
- 3 defined pass types: Correctness, Clarity, Consistency
Files
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:
1. Correctness - run tests, fix failures 2. Clarity - code readability and structure 3. Consistency - naming, patterns, style alignment 4. 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
1. Initialize state file (or load existing) 2. Determine next unconverged dimension 3. Dispatch subagent for that dimension 4. Record results in state file 5. If dimension converged (0 issues), mark it 6. If all dimensions converged or 10 passes reached, stop 7. 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
Pass Type Definitions
Pass 1: Correctness
Goal: Code works as intended.
Scope:
- Run test suite, identify failures
- Fix failing tests
- Check for runtime errors
- Verify edge cases specified in requirements
Agent prompt focus: "Run all tests. For each failure, identify the root cause and fix it. Do not refactor; focus only on making tests pass."
Tools: Bash (pytest/test runner), Edit
Convergence: 0 test failures
Pass 2: Clarity
Goal: Code is readable and well-structured.
Scope:
- Variable and function naming
- Function length and complexity
- Comment quality (helpful vs. noise)
- Dead code removal
- Single-responsibility adherence
Agent prompt focus: "Review for readability. Rename unclear variables, break up long functions, remove dead code. Do not change behavior."
Tools: Read, Edit, pensive:code-refinement
Convergence: 0 clarity issues found by reviewer
Pass 3: Consistency
Goal: Code follows project conventions.
Scope:
- Naming conventions (snake_case, camelCase, etc.)
- Import ordering
- Error handling patterns
- Logging patterns
- File organization
Agent prompt focus: "Compare against codebase conventions. Flag deviations from established patterns. Use style-gene-transfer if exemplar available."
Tools: Read, Grep, Edit
Convergence: 0 convention deviations found
Pass 4: Polish
Goal: Code is production-ready.
Scope:
- Error messages are user-friendly
- Documentation is accurate and complete
- Edge cases have graceful handling
- Configuration is well-documented
Agent prompt focus: "Review error messages, docs, and edge cases. Ensure each error message helps the user understand what went wrong and how to fix it."
Tools: Read, Edit
Convergence: 0 polish issues found
Pass Ordering
Passes run in order: correctness, clarity, consistency, polish. This ordering is intentional:
1. Fix bugs before cleaning up code 2. Clean up code before checking conventions 3. Check conventions before polishing edges
If a pass in a later dimension discovers a bug (correctness regression), surface to human rather than re-running the converged correctness pass.
Related skills
How it compares
Defines pass boundaries for a polishing stack, not a single-shot “fix all code review comments” prompt.
FAQ
Who is dorodango for?
Developers running the attune dorodango workflow who need crisp pass definitions so agents fix tests first, then clarity, then consistency.
When should I use dorodango?
After build backend work when tests exist, during ship review before merge, and during ship testing when you want correctness pass before style passes.
Is dorodango safe to install?
Passes assume Bash test runs and file edits; review the Security Audits panel on this Prism page and sandbox test commands appropriately.