Coordinate multiple agents executing bead-based plans with a lead worker model.
npx skills add https://github.com/cmtkdot/arc --skill team-cmtkdot
Please help me install this Agent Skill. Skill: team Source: https://github.com/cmtkdot/arc/tree/main/skills/team Command: npx skills add https://github.com/cmtkdot/arc --skill team-cmtkdot
Coordinated multi-agent execution with a lead agent and self-claiming workers helps manage large, dependency-rich workflows by coordinating tasks, avoiding conflicts, and enforcing order.
Start team-mode execution by running the interactive command /arc-start in your target repository.
High-intent search queries and answers about installing and using this skill.
Multi-agent orchestration coordinates a lead agent with self-claiming workers to execute complex plans, managing task dependencies and avoiding shared-file conflicts. It uses a lead-worker model with gate-driven checkpoints to enforce strict orderings.
The lead-worker model assigns a lead agent to coordinate self-claiming workers across large dependency-rich workflows. It enforces TDD-ordering and uses a team ledger at .arc/team-ledger.json to track progress and ensure resilient execution.
Start team-mode execution by running the interactive command /arc-start in your target repository. This initiates the coordinated multi-agent workflow using bead governance primitives like locking, pinning, and gates.
Yes, multi-agent team execution requires the team environment flag CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 to be set. This enables the coordinated lead-worker functionality and bead governance primitives.
Multi-agent orchestration is best suited for large, interdependent projects where shared-file conflicts and strict orderings must be managed. It excels at complex bead graphs and mixed dependencies requiring gate-based checkpoints.
Yes, multi-agent orchestration provides gate-based checkpoints and shared-file conflict resolution to keep work moving. Bead governance primitives like locking and pinning enforce predictable execution across coordinated agents.
alinaqiOrchestrate AI agents through a strict TDD pipeline to create pull requests.
anionzoCoordinate multiple worker agents executing beads with rescue coordination via Agent Mail.
curiositechCoordinate multiple AI agents on shared codebases using git worktrees and file locking.
faisalanjumCreate multi-agent teams with interdependent tasks and spawn teammates for automated testing.
