Delegate inline task lists to subagents with dependency-aware parallel execution.
npx skills add https://github.com/tkersey/dotfiles --skill mesh
Please help me install this Agent Skill. Skill: mesh Source: https://github.com/tkersey/dotfiles/tree/main/codex/skills/mesh Command: npx skills add https://github.com/tkersey/dotfiles --skill mesh
This Skill addresses the challenge of coordinating multiple tasks by delegating work to spawned subagents, enabling parallel execution while preserving correct ordering through dependency-aware waves.
Invoke the mesh skill with an inline task list using the $mesh command in your message. For example, provide a list of tasks; then reply with $mesh confirm to run exactly this task list (no copy/paste).
High-intent search queries and answers about installing and using this skill.
To execute parallel tasks with dependency management, provide an inline task list and invoke the mesh orchestrator, which spawns worker subagents to execute tasks in dependency-respecting waves. The orchestrator schedules tasks, monitors liveness, and validates post-step results while workers handle implementation.
Dependency-aware parallel execution is an orchestration mechanism that groups tasks into sequential waves, ensuring dependent tasks only run after their prerequisites complete. It coordinates spawned worker subagents to handle parallel workloads while preserving correct execution order and validating each step.
To start an automated multi-step workflow, invoke the mesh skill with an inline task list using the $mesh command in your message. Reply with $mesh confirm to execute that exact task list without copy/pasting, allowing the orchestrator to delegate implementation work to spawned worker subagents.
No, the orchestrator is forbidden from executing tasks directly unless explicitly authorized by the user. It handles planning, liveness monitoring, and post-step validation, while delegating actual task implementation to spawned worker subagents to maintain safe orchestration boundaries.
Use parallel worker subagents for large task batches, patch/apply workflows, and automated multi-step operations that require worker tooling. It is ideal when you have an explicit task list that benefits from dependency-respecting parallel execution with per-task commits and post-step validation.
Yes, dependency-respecting parallel execution ensures tasks run in an order that honors dependencies and performs commits and validation per step. The orchestrator manages post-step validation after each worker subagent completes its assigned task within the execution wave.
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