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xuzeyu91

distributed-task-orchestrator

by xuzeyu91

WebCode is a browser-based AI coding platform that lets you remotely run CLI assistants like Claude Code and Codex. Code anywhere with just a web browser. We’re also adding an office-assistant mode for planning, research/summaries, meeting notes, and drafting docs/emails—connected to your project context.

282🍴 25📅 Jan 23, 2026

SKILL.md


name: distributed-task-orchestrator description: Decompose complex tasks into parallel sub-agents. Use for multi-step operations, batch processing, or when user mentions "parallel", "agents", or "orchestrate".

Distributed Task Orchestrator

You are an advanced distributed task orchestration system. Decompose complex requests into independent atomic tasks, manage parallel execution, and aggregate results.

Quick Decision

Is task complex? (3+ independent steps, multiple files, parallel benefit)
├── NO → Execute directly, skip orchestration
└── YES → Use orchestration
    ├── Simulated mode (default) → Present as parallel batches
    └── CLI mode (user requests) → Launch real Claude CLI sub-agents

Skip orchestration for: single-file ops, simple queries, < 3 steps, purely sequential tasks.

Core Workflow

Phase 1: Decompose

Analyze request → Break into atomic tasks → Map dependencies → Create .orchestrator/master_plan.md

# Task Plan

## Request
> [Original request]

## Tasks
| ID | Task | Deps | Status |
|----|------|------|--------|
| T-01 | [Description] | None | 🟡 |
| T-02 | [Description] | T-01 | ⏸️ |

Status: 🟡 Pending · 🔵 Running · ✅ Done · ❌ Failed · ⏸️ Waiting

Phase 2: Assign Agents

Create .orchestrator/agent_tasks/agent-XX.md for each task:

# Agent-XX: [Task Name]
**Input:** [parameters]
**Do:** [specific instructions]
**Output:** [expected format]

Phase 3: Execute

Simulated Mode (Default):

═══ Batch #1 (No Dependencies) ═══
🤖 Agent-01 [T-01: Task Name]
   ⚙️ [Execution steps...]
   ✅ Completed

═══ Batch #2 (After Batch #1) ═══
🤖 Agent-02 [T-02: Task Name]
   ⚙️ [Execution steps...]
   ✅ Completed

CLI Mode (When Requested):

# Windows - Parallel execution
$jobs = Get-ChildItem ".orchestrator/agent_tasks/*.md" | ForEach-Object {
    Start-Job -ScriptBlock {
        param($path, $out)
        claude --print (Get-Content $path -Raw) | Out-File $out
    } -ArgumentList $_.FullName, ".orchestrator/results/$($_.BaseName)-result.md"
}
$jobs | Wait-Job | Receive-Job; $jobs | Remove-Job
# Linux/Mac - Using GNU parallel
parallel claude --print "$(cat {})" ">" .orchestrator/results/{/.}-result.md ::: .orchestrator/agent_tasks/*.md

Phase 4: Aggregate

Collect results → Merge by dependency order → Generate .orchestrator/final_output.md

# Execution Report
- Tasks: N total, X succeeded, Y failed
- Duration: Zs

## Results
[Integrated findings organized logically]

## Key Takeaways
1. [Finding 1]
2. [Finding 2]

Dependency Patterns

  • Parallel: T-01, T-02, T-03 → T-04 (first three run together)
  • Serial: T-01 → T-02 → T-03 (each waits for previous)
  • DAG: Complex graphs use topological sort

Error Handling

StrategyWhen to Use
Retry (3x, exponential backoff)Timeouts, transient failures
Skip and continueNon-critical tasks
Fail-fastCritical dependencies

Best Practices

  1. Granularity: Target 1-5 min per task; split large, merge trivial
  2. Parallelism: Minimize dependencies; use file-based data passing
  3. State: Update master_plan.md on every status change

Trigger Conditions

USE when:

  • 3+ independent steps possible
  • User mentions: "parallel", "concurrent", "subtasks", "agents"
  • Batch processing needed
  • Claude CLI sub-agents requested

SKIP when:

  • Single-step task
  • Quick query/explanation
  • Purely sequential with no parallel benefit

Score

Total Score

85/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

+5
最近の活動

1ヶ月以内に更新

+10
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10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

+5
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プログラミング言語が設定されている

+5
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1つ以上のタグが設定されている

+5

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