distributed-task-orchestrator
Splits complex projects into parallel agent workflows.
Install
mkdir -p .claude/skills/distributed-task-orchestrator && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7664" && unzip -o skill.zip -d .claude/skills/distributed-task-orchestrator && rm skill.zipInstalls to .claude/skills/distributed-task-orchestrator
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Decompose complex tasks into parallel sub-agents. Use for multi-step operations, batch processing, or when user mentions "parallel", "agents", or "orchestrate".Key capabilities
- →Decompose complex requests into independent atomic tasks
- →Create master execution plans with dependency mapping
- →Manage parallel execution of sub-agents
- →Aggregate results from multiple sub-tasks into a final report
How it works
The skill analyzes a request to create a master plan, assigns atomic tasks to sub-agents, executes them in parallel or series based on dependencies, and merges the final output.
Inputs & outputs
When to use distributed-task-orchestrator
- →Decompose a large feature implementation
- →Orchestrate batch refactoring across multiple files
- →Manage multi-step migration tasks
About this skill
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
| Strategy | When to Use |
|---|---|
| Retry (3x, exponential backoff) | Timeouts, transient failures |
| Skip and continue | Non-critical tasks |
| Fail-fast | Critical dependencies |
Best Practices
- Granularity: Target 1-5 min per task; split large, merge trivial
- Parallelism: Minimize dependencies; use file-based data passing
- State: Update
master_plan.mdon 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
- workflow.md - Detailed workflow spec
- templates.md - Complete templates
- cli-integration.md - CLI deep dive
- examples.md - Practical examples
When not to use it
- →For single-file operations or simple queries
- →For tasks with fewer than 3 steps
- →For purely sequential tasks without parallel benefit
Limitations
- →Requires tasks to be divisible into independent atomic units
- →Performance depends on the granularity of the task decomposition
How it compares
It automates the decomposition and parallel management of tasks that would otherwise require manual step-by-step execution.
Compared to similar skills
distributed-task-orchestrator side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| distributed-task-orchestrator (this skill) | 1 | 7mo | Review | Advanced |
| autonomous-agents | 10 | 6mo | No flags | Advanced |
| agent-goal-planner | 2 | 6mo | No flags | Advanced |
| planner | 1 | 6mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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