skills/ultrawork/SKILL.md
Use when you need to complete tasks quickly with parallel agent execution.
npx skillsauth add seokan-jeong/team-shinchan team-shinchan:ultraworkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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👦 [Shinnosuke] Ultrawork mode -- maximum parallelization!
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If args > 2000 chars: truncate + warn.
If args contains a recognized preset name, resolve agent list from agents/_shared/team-presets.json:
node -e "
const fs = require('fs');
const presets = JSON.parse(fs.readFileSync('${CLAUDE_PLUGIN_ROOT}/agents/_shared/team-presets.json', 'utf8')).presets;
const input = process.argv[1] || '';
const matched = Object.values(presets).find(p => input.toLowerCase().includes(p.name));
if (matched) console.log(JSON.stringify(matched));
" "{args}"
agents array to constrain which domain agents are assigned in Step 3Recognized preset names: fullstack, backend-api, quality, data-pipeline, security-audit
Task(subagent_type="team-shinchan:nene", model="opus",
prompt="ULTRAWORK rapid planning. Minimal breakdown: task units, file ownership per agent, dependency order, parallelizable groups. Under 30 lines.\nUser request: {args}")
Store as {plan_context}. Skip if task is clear and touches 1-2 files.
If {plan_context} was generated, compute Wave execution order using ontology:
node -e "
const { getWaveOrder } = require('${CLAUDE_PLUGIN_ROOT}/src/ontology-engine.js');
const taskList = /* parse task units from plan_context as [{id, files:[...]}] */;
const { waves, warnings } = getWaveOrder(process.cwd(), taskList);
console.log(JSON.stringify({ waves, warnings }, null, 2));
"
waves = [[task1, task2], [task3], ...] — 같은 Wave 내 태스크는 병렬 실행 가능getWaveOrder가 단일 Wave를 반환하거나 온톨로지가 없으면, 모든 태스크를 동시 병렬 실행 (기존 동작 유지)Store result as {wave_plan}. Pass to Step 3 execution.
Task(subagent_type="team-shinchan:shinnosuke", model="opus",
prompt="/team-shinchan:ultrawork invoked.
${plan_context ? 'Pre-planned:\n' + plan_context : ''}
Parallel execution:
1. Break into independent units (or follow plan)
2. Assign to agents in parallel (run_in_background=true)
Routing: Analysis→Shiro/Misae/Hiroshi | Execution→Bo/Kazama | Frontend→Aichan | Backend→Buriburi | DevOps→Masao | Verification→Action Kamen
3. Queue sequential tasks, wait for completion
4. Integrate results + Action Kamen verification
Done when: all TODOs complete, features working, tests pass, no errors. Keep working if not met.
User request: ${args}")
STOP HERE. The above Task handles everything.
After all parallel agents complete:
Run: node src/stagnation-detector.js --jsonl .shinchan-docs/work-tracker.jsonl --window 20
If stagnation: true, surface findings in the summary before handing off to Action Kamen:
"Stagnation patterns detected: {pattern names} — {evidence}. Reviewing before AK handoff."
testing
Default-on interview option-quality panel — N diverse generators produce structure-free options, a SelfCheckGPT majority-vote consensus filters hallucinations, a SteerConf cautious-confidence judge scores survivors, and a deterministic top-K is returned. Workflow tier; the single fierce-* skill that is ON by default.
development
Deterministic adversarial code review for high-stakes scope — independent per-dimension review, a non-skippable per-finding refutation, completeness + interaction critics, and a deterministic 3-lens rubric judge panel. Opt-in main-loop Workflow tier.
data-ai
Deterministic loop-until-done for high-stakes long-running tasks — a worker/verifier loop the script bounds by iteration cap, token budget, and stagnation, closed by an Action-Kamen gate. Opt-in main-loop Workflow tier.
testing
Deterministic adversarial debate for high-stakes or irreversible decisions — mandatory refutation plus a scored judge panel. Opt-in main-loop Workflow tier.