/dev-team
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.
$ npx -y skills add evolution-foundation/evo-nexus --skill dev-team --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/dev-team
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
dev-team.SKILL.mdname: dev-team
description: 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.
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)
Read more
name: dev-team description: 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.
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)
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