shuyu-labs/webcode/distributed-task-orchestrator

Claude Code and agent skill by shuyu-labs/webcode

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Decompose complex tasks into parallel sub-agents. Use for multi-step operations, batch processing, or when user mentions "parallel", "agents", or "orchestrate".

Install

npx vskill@latest install shuyu-labs/webcode/distributed-task-orchestrator

SKILL.md

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

markdown
# 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:

markdown
# 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):

powershell
# 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; $jobs | Remove-Job
bash
# Linux/Mac - Using GNU parallel
parallel claude --print "$(cat {})" ">" .orchestrator/results/{/.}-result.md ::: .orchestrator/agent_tasks/*.md
Phase 4: Aggregate

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

markdown
# 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

Related Files

Security

  • Security scanPassed, 0 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
285
Repository forks
45
7-day trend score
28

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 20 Mar 2026, 7 months ago.

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