← ClaudeAtlas

agent-swarmlisted

(Industry standard: Parallel Agent) Primary Use Case: Work that can be partitioned into independent sub-tasks running concurrently across multiple agents. Parallel multi-agent execution pattern. Use when: work can be partitioned into independent tasks that N agents can execute simultaneously across worktrees. Includes routing (sequential vs parallel), merge verification, and correction loops.
richfrem/agent-plugins-skills · ★ 3 · AI & Automation · score 62
Install: claude install-skill richfrem/agent-plugins-skills
## Dependencies This skill requires **Python 3.8+** and standard library only. No external packages needed. **To install this skill's dependencies:** ```bash pip-compile ./requirements.in pip install -r ./requirements.txt ``` See `../../requirements.txt` for the dependency lockfile (currently empty — standard library only). --- # Agent Swarm Parallel or pipelined execution across multiple agents and worktrees. The orchestrator partitions work, dispatches to agents, and verifies/merges the results. ## When to Use - Large features that can be split into independent work packages - Bulk operations (tests, docs, migrations, RLM distillation) that benefit from parallelism - Multi-concern work where specialists handle different aspects simultaneously ## Process Flow 1. **Plan & Partition** -- Break work into independent tasks. Define boundaries clearly. 2. **Route** -- Decide execution mode: - **Sequential Pipeline** -- Tasks depend on each other (A -> B -> C) - **Parallel Swarm** -- Tasks are independent (A | B | C) 3. **Dispatch** -- Create a worktree per task. Assign each to an agent: - CLI agent (Claude, Gemini, Copilot) - Deterministic script - Human 4. **Execute** -- Each agent works in isolation. No cross-worktree communication. 5. **Verify & Merge** -- Orchestrator checks each worktree's output against acceptance criteria. - **Pass** -> Merge into main branch - **Fail** -> Generate correction packet, re-dispatch 6. **Seal** -- Bundle all merged