Coordinate parallel bead execution across agent workers with phase calibration.
npx skills add https://github.com/eaasxt/Farmhand --skill execute-eaasxt
Please help me install this Agent Skill. Skill: execute Source: https://github.com/eaasxt/Farmhand/tree/main/config/skills/execute Command: npx skills add https://github.com/eaasxt/Farmhand --skill execute-eaasxt
Coordinating multiple agent workers to execute work items (beads) in parallel while preserving file scope and avoiding conflicts, ensuring efficient throughput and controlled collaboration.
Run /execute to start orchestration of ready beads across parallel tracks.
High-intent search queries and answers about installing and using this skill.
Parallel execution across multiple agent workers is coordinated by grouping work items into non-overlapping file scopes called tracks. This track-based parallelism allows concurrent execution while preserving safe file scope and avoiding conflicts.
Bead-based orchestration is a coordination method that sequences work items across dependencies using phase-based planning. It applies to AI agent workflows where phases, tracks, and calibration are required to optimize throughput.
You start orchestrating ready beads by running the /execute command. This initiates the orchestration process, which includes worker spawning per track and Agent Mail coordination for efficient throughput.
Error recovery during parallel agent worker execution applies phase boundary calibration to gracefully recover and re-plan when blocks occur. This failure handling ensures work continues safely when interruptions happen.
Phase boundary calibration is needed when sequencing beads across dependencies in multi-phase planning. It ensures safe transitions between phases and supports re-planning when blocks or failures occur during concurrent execution.
Yes, Agent Mail coordination is implemented specifically to support track-based parallelism in AI agent workflows. It manages communication between spawned workers to maintain controlled collaboration and optimize throughput.
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