skills.rest
curiositech
curiositechOFFICIAL
Explore all skills by this author →
WebsiteGitHub

dag-parallel-executor

Orchestrates parallel DAG wave execution with configurable concurrency and task coordination.

10|1|Updated Mar 17, 2026
Search Tags:#workflow#concurrency#orchestration#dag#parallel-execution#task-tool
One-click install
npx skills add https://github.com/curiositech/windags-skills --skill dag-parallel-executor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dag-parallel-executor
Source: https://github.com/curiositech/windags-skills/tree/main/skills/dag-parallel-executor
Command: npx skills add https://github.com/curiositech/windags-skills --skill dag-parallel-executor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates the execution of DAG waves with controlled concurrency, ensuring reliable parallel task processing and predictable resource usage, while coordinating spawned agents and maintaining state across waves.

Core Features & Use Cases

  • Wave-based parallel execution with configurable max parallelism to respect resource limits.
  • Agent spawning and task coordination via Claude's Task tool to scale DAG processing across node types.
  • Robust error handling, retry strategies, and failure management with clear telemetry for schedulers and aggregators.
  • Integrations with dag-task-scheduler, dag-result-aggregator, and dag-context-bridger to form a cohesive DAG ecosystem.

Quick Start

Run a sample DAG with parallel waves to observe concurrency limits and coordination in action.

Frequently Asked Questions about dag-parallel-executor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I execute parallel tasks in a DAG workflow with controlled concurrency?▼

Parallel tasks in a DAG workflow are executed in deterministic waves with configurable max parallelism to enforce resource limits. This approach ensures reliable parallel processing and predictable resource usage across complex dependency graphs.

What is wave-based parallel execution for DAG orchestration?▼

Wave-based parallel execution is a method that processes DAG nodes in synchronized batches, ensuring deterministic wave progression. It coordinates sub-agents via the Task tool while enforcing parallelism limits and batching for reliable result collection.

How do I handle failures and timeouts when running concurrent DAG workflows?▼

Concurrent DAG workflows handle failures and timeouts through robust error handling, retry strategies, and clear telemetry. The system maintains state across waves and coordinates spawned agents to manage failures reliably.

Can I scale DAG processing across different node types using sub-agent coordination?▼

DAG processing scales across node types by spawning and coordinating sub-agents via the Task tool. This allows parallel execution to distribute work across different agents while maintaining wave progression and enforcing parallelism limits.

When do I need resource budgeting for parallel task execution in workflows?▼

Resource budgeting for parallel task execution is needed when workflows require controlled concurrency to respect resource limits. It ensures deterministic wave progression and prevents overwhelming resources during complex DAG processing.

Related Skills

Explore More Software Engineering Skills→
curiositechcuriositech
10

dag-task-scheduler

Generates wave-based execution plans for DAG tasks with resource constraints.

Official
Advanced
curiositechcuriositech
10

dag-result-aggregator

Merge parallel DAG branch outputs into a single structured result.

Official
Advanced
curiositechcuriositech
10

next-move

Predict a five-node meta-DAG of high-impact skills from git state and project context.

Official
Advanced
pwarnockpwarnock
2

subagent-coordination

Define agent roles, delegate tasks, and orchestrate multi-agent workflows.

Community
Advanced