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dev-team

@evolution-foundation · 收录于 5 天前 · 上游提交 2 个月前

On-demand spawning of multiple engineering agents in parallel for large-context work. Use when a task is too big for a single agent and the work can be split into independent streams.

适合你,如果单个智能体处理不了你的大型工程任务。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add evolution-foundation/evo-nexus/dev-team
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- evolution-foundation/evo-nexus/dev-team
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify evolution-foundation/evo-nexus/dev-team
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 7f5dd76 · 表述以原文为准
它做什么

Claude 会将大任务拆成多个独立子任务,同时启动多个工程智能体并行工作,最后合并结果输出。

什么时候触发

当任务对单个智能体太大且可拆分为独立流时触发,例如多文件重构、代码库审计、性能调查等。

装好后可以这样说
触发多个智能体并行审计。
同时执行两个流。
并行分析不同方面。
技能原文 SKILL.md作者撰写 · Apache-2.0 · 7f5dd76

Dev Team

Derived from oh-my-claudecode (MIT, Yeachan Heo). Adapted for the EvoNexus Engineering Layer.

On-demand parallel agent spawning. When a task is too big for one agent and the work can be split into independent streams, spin up multiple engineering agents working in parallel.

Use When
  • Multi-file refactor across 10+ files in different modules
  • Codebase audit that benefits from parallel exploration
  • Performance investigation across multiple subsystems
  • Documentation pass across many files
Do Not Use When
  • Sequential dependencies (B needs A's output)
  • Single-file change
  • Task fits within a single agent's context
Workflow
  1. Decompose the task into N independent streams
  2. Assign each stream to the most appropriate agent (apex / bolt / lens / etc.)
  3. Spawn agents in parallel via Task tool
  4. Collect results as they return
  5. Synthesize into a unified output
  6. Save to workspace/development/research/[C]team-{topic}-{date}.md
Streams Example

For "audit the entire auth module":

  • Stream 1: @scout-explorer → map all auth files
  • Stream 2: @vault-security → security audit
  • Stream 3: @lens-reviewer → code quality review
  • Stream 4: @grid-tester → test coverage analysis
  • Stream 5: @apex-architect → architecture analysis

All spawn in parallel, results combine into one report.

Output
## Team Investigation — {topic}

### Streams
1. {stream 1 result summary}
2. {stream 2 result summary}
...

### Cross-stream Findings
[Insights that emerged from combining results]

### Recommendation
[Unified next step]
Pairs With
  • Any of the 19 engineering agents (you pick which to spawn)
  • dev-autopilot (which can spawn its own team internally)
  • @compass-planner (often the consumer of team output)
按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →

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