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agentica-spawn

@parcadei · 收录于 1 周前 · 上游提交 5 个月前

Spawn Agentica multi-agent patterns

适合你,如果需要编排多个智能体协同完成任务

/ 下载安装
agentica-spawn.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add parcadei/continuous-claude-v3/agentica-spawn
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- parcadei/continuous-claude-v3/agentica-spawn
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify parcadei/continuous-claude-v3/agentica-spawn
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 d07ff4b · 表述以原文为准
它做什么

装上后,Claude 能根据你选的多智能体模式(如群组、层级等),自动创建多个AI角色协作完成任务,并汇总结果。

什么时候触发

当Claude询问你选择哪种多智能体模式,或你主动要求使用群组、层级等模式时触发。

装好后可以这样说
Claude会创建三个专家角色并行分析并合并结果。
Claude会分解任务,由规划、编码、审查角色协作完成。
技能原文 SKILL.md作者撰写 · MIT · d07ff4b

Agentica Spawn Skill

Use this skill after user selects an Agentica pattern.

When to Use
  • After agentica-orchestrator prompts user for pattern selection
  • When user explicitly requests a multi-agent pattern (swarm, hierarchical, etc.)
  • When implementing complex tasks that benefit from parallel agent execution
  • For research tasks requiring multiple perspectives (use Swarm)
  • For implementation tasks requiring coordination (use Hierarchical)
  • For iterative refinement (use Generator/Critic)
  • For high-stakes validation (use Jury)
Pattern Selection to Spawn Method
Swarm (Research/Explore)
swarm = Swarm(
    perspectives=[
        "Security expert analyzing for vulnerabilities",
        "Performance expert optimizing for speed",
        "Architecture expert reviewing design"
    ],
    aggregate_mode=AggregateMode.MERGE,
)
result = await swarm.execute(task_description)
Hierarchical (Build/Implement)
hierarchical = Hierarchical(
    coordinator_premise="You break tasks into subtasks",
    specialist_premises={
        "planner": "You create implementation plans",
        "implementer": "You write code",
        "reviewer": "You review code for issues"
    },
)
result = await hierarchical.execute(task_description)
Generator/Critic (Iterate/Refine)
gc = GeneratorCritic(
    generator_premise="You generate solutions",
    critic_premise="You critique and suggest improvements",
    max_rounds=3,
)
result = await gc.run(task_description)
Jury (Validate/Verify)
jury = Jury(
    num_jurors=5,
    consensus_mode=ConsensusMode.MAJORITY,
    premise="You evaluate the solution"
)
verdict = await jury.decide(bool, question)
Environment Variables

All spawned agents receive:

  • SWARM_ID: Unique identifier for this swarm run
  • AGENT_ROLE: Role within the pattern (coordinator, specialist, etc.)
  • PATTERN_TYPE: Which pattern is running
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

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