dorodango

dorodango is a skill for Claude Code from athola/claude-night-market. It costs 31 tokens per session (1,033 once invoked), scanned A, original, MIT.

A code-polishing workflow that makes repeated passes over working code for correctness, clarity, consistency, and final details.

In plain words
What is it for?
Use it to refine code before review or release, improve readability and naming, align code with project conventions, and tighten documentation and edge cases.
Why use it?
It gives review a repeatable structure after the code already works and its tests pass. Each pass focuses on a different kind of improvement.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the attune plugin — 14 skills, 11 commands, 2 agents shipped together

Good fit Use it to refine code before review or release, improve readability and naming, align code with project conventions, and tighten documentation and edge cases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/athola/claude-night-market/dorodango
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add athola/claude-night-market --skill dorodango
Clone the repo
git clone --depth 1 https://github.com/athola/claude-night-market

Made for: Claude Code.

Or install attune, the plugin that ships this one along with the rest of its 14 skills, 11 commands, 2 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dorodango

README.md
[![agentmods](https://agentmods.dev/badge/skills/athola/claude-night-market/dorodango/github.svg)](https://agentmods.dev/skills/athola/claude-night-market/dorodango)
Your own site
<a href="https://agentmods.dev/skills/athola/claude-night-market/dorodango"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/dorodango/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dorodango

Your own site · 80×15
<a href="https://agentmods.dev/skills/athola/claude-night-market/dorodango"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/dorodango.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,033 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.01033
Opus 5 $0.00015 $0.00517
Sonnet 5 $0.00006 $0.00207
Haiku 4.5 $0.00003 $0.00103

Measured 8d ago against content hash dd9002d4e7c6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

dorodango scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/attune/skills/dorodango/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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: 0 marks 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.

Read the full file on GitHub · 143 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 143 lines · 31 tokens per session scan A dd9002d4e7c6

Subscribe to this mod's changes

dorodango is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,033 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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