Execute dependency-aware plan files with parallel AI worker subagents.
npx skills add https://github.com/Dethon/ai-dev-flow --skill plan-swarm
Please help me install this Agent Skill. Skill: plan-swarm Source: https://github.com/Dethon/ai-dev-flow/tree/main/skills/plan-swarm Command: npx skills add https://github.com/Dethon/ai-dev-flow --skill plan-swarm
This Skill enables teams to orchestrate a swarm of AI workers to execute complex, dependency-aware plans, accelerating delivery while preserving correct sequencing and retry handling.
Run the swarm on a plan file, optionally specifying concurrency and model. Example: /plan-swarm docs/plans/sample-plan.md --workers 3 --model opus
High-intent search queries and answers about installing and using this skill.
To coordinate parallel AI workers, you can use a task orchestration skill that spawns concurrent subagents, enforces dependency order constraints, and monitors retries until all exit criteria are met.
Running a plan file with dependency awareness requires a centralized orchestrator that creates a deterministic task graph, spawns workers up to your specified limit, and handles failures with automatic retries.
Yes, you can specify a concurrency limit for AI workers by passing a worker count parameter, ensuring the swarm processes parallelizable tasks concurrently while respecting serial order constraints.
Dependency-aware task orchestration handles final validation by using a centralized monitor that tracks the task graph execution and ensures all defined exit criteria are fully met before completing the process.
You should use parallel processing for multi-step plan execution when your plan contains tasks that can run concurrently alongside tasks requiring strict serial ordering, retries, and centralized dependency tracking.
danielkhigayGenerate a multi-agent construction plan with dependency graphs and verification commands.
MadAppGangGenerate screenshots, test results, and deployment logs with confidence scoring.
josipmusaExecute confirmed implementation plans by dispatching isolated subagents with rubber-duck verification.
ed3daiExecute implementation plans phase-by-phase with subagent task dispatch and code review.
