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2026年10月5日 收录
  1. X · @RoundtableSpace

    Claude Code 自治智能体团队工作区配置方案

    用 teams 角色、git worktree 隔离、文件锁与对手评审,把 Claude Code 配成多智能体协作团队。

    Configure my Claude Code workspace for autonomous agent teams:
    
    In ~/.claude/teams, create the missing roles. Workers run on Sonnet (medium effort) in separate git worktree branches. The adversary runs on Fable.
    In ~/.claude/settings.json, set CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 and lock the main session to effortLevel: high.
    Initialize tasks.json with file-level locking so workers can coordinate directly.
    In CLAUDE.md, require an adversary review before any PR.
    
    Show me the config diffs before applying anything.

    提示词 · 多智能体 · Agent 工程 · 工作流配置 · 代码审查 · 研发效能

  2. X · @pushpak1300图片

    用 Opus 多智能体编排做全仓库重构审查

    作者分享让编排器调度只读子智能体扫描全仓库,产出真实重构建议而非 AI 挑刺的用法。

    New favourite use case for opus 5.5:
    
    Give them the whole repo and ask:
    
    “Tell me what we should actually refactor.”
    
    • an orchestrator maps the architecture and conventions
    • it sends fresh read-only agents through every subsystem
    • it validates, dedupes, and ranks the findings
    
    The result: real code smells, dead code, duplication, and architecture issues instead of unnecessary AI nitpicks.
    
    Prompt 👇
    用 Opus 多智能体编排做全仓库重构审查 的效果图用 Opus 多智能体编排做全仓库重构审查 的效果图

    提示词 · 软件工程提示词 · 代码重构 · 多智能体 · 架构分析 · 研发效能

  3. X · @minchoi图片

    用总控提示词打造 Grok AI 幕僚长

    通过总控提示词统一调度多个 Bot,强调来源核验、行动审批与持续改进。

    This Grok Bot prompt is literally $300/hr chief of staff https://t.co/dxLaVtmXVJ
    用总控提示词打造 Grok AI 幕僚长 的效果图

    提示词 · 助手提示词 · Agent 工程 · 多智能体 · 工作流

  4. X · @Voxyz_ai

    让并行子代理把复杂任务推进到交付

    一套面向 Codex 的端到端提示词,强调并行分工、持续验证与最终闭环。

    ok this one is stupidly good. try it on 5.6 sol extra high in codex!
    
    it plays straight into codex's new strengths, parallel subagents and computer use, and lets 5.6 sol carry a goal all the way to done.
    
    the prompt 👇
    
    I have one complete task to push end to end: [your spec doc, or the full task in detail]. treat it as one end-to-end goal: 𝘁𝗮𝗸𝗲 𝘁𝗵𝗲 𝘄𝗵𝗼𝗹𝗲 𝗽𝗹𝗮𝗻 𝘁𝗼 𝗱𝗼𝗻𝗲, until architecture, implementation, tests, review and the final result all clear the bar. break the goal into independent parts, spawn as many parallel agents as it takes, and give each one its own goal with a clear deliverable, a verification method, and done criteria.
    
    then run it like an operator: schedule the agents in parallel, track progress, synthesize what comes back, resolve conflicts, keep implementing, verify live after every important step, review when it matters, commit when it's ready, and close with a final summary. verification must cover the real end-to-end path: browser and computer use, clicks, keyboard, whatever it takes. don't stop at partial progress unless you're blocked by missing credentials, destructive ambiguity, or conflicting requirements.

    提示词 · 软件工程提示词 · Agent 工程 · 多智能体 · 端到端交付 · 测试验证 · 代码审查

  5. X · @LinearUncle图片

    Harness 互拷与追问式共识构建

    用双 Harness 角色分工和 16 轮追问,把个人判断沉淀为共享理解文档。

    做了一个有趣的实验,/grill-me (拷问我),如果这个“我”是AI 会怎么样?
    
    也就是用A harness来拷贝我,B  harness来代替人类回答问题。
    
    herdr 真的是伟大的发明,天生支持Harness之间互相调用。
    
    提示词:
    
    1.  /herdr 开右边pane,启动grok
    2. read grill-me skill, understand it. 你扮演人类回答问题,在右侧使用/grill-me skill,我们的目标是clone https://t.co/Wdm7I47qfW
    
    最后问了 16 个问题达成共识,形成文档,效果还不错。😂
    
    当然我感觉可以改进下/grill-me skill,让subagent来回答。
    Harness 互拷与追问式共识构建 的效果图Harness 互拷与追问式共识构建 的效果图

    提示词 · 助手提示词 · 技能 · Agent 工程 · AI 应用 · 多智能体 · 实验

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