Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Claude Code Agent Teams
Coordinate multiple Claude Code agents to work in parallel on independent tasks like multi-lens reviews, debugging, and full-stack features with defined file...
skill openclawclawhub Free
Coordinate multiple Claude Code agents to work in parallel on independent tasks like multi-lens reviews, debugging, and full-stack features with defined file...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, RESEARCH-SYNTHESIS.md, SKILL.md, package.json, scripts/team-cleanup.sh, scripts/team-monitor.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- matthew-a-gordon
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Claude Code Agent Teams
Orchestrate multiple Claude Code agents working together on complex tasks. Agents coordinate through a shared task list, message each other directly, and work in parallel on independent scopes.
When to Use
β Use for parallel independent work: Multi-lens code reviews (security, performance, tests in parallel) Debugging with competing hypotheses (test theories simultaneously) Full-stack features (frontend/backend/tests by separate specialists) Architecture decisions (adversarial debate produces stronger ADRs) Cross-domain investigations (bottleneck analysis across systems) Data-parallel work (inventory classification, bulk refactoring) β Don't use for: Sequential work with tight dependencies Same-file edits (conflict risk) Simple tasks (coordination overhead > benefit) Learning/exploration (single agent with full context is better) Rule of thumb: Teams multiply token cost 3-4x. Use only when parallelization benefit exceeds coordination overhead.
1. Enable Feature
Environment variable: export CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 Or settings file (~/.claude/settings.json): { "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" } }
2. Validate Setup
./scripts/validate-setup.sh Checks for: env var set, claude CLI available, tmux installed (optional).
3. Pick Template
TemplateUse Caseparallel-review.mdMulti-lens code review (security + performance + tests)competing-hypotheses.mdDebug by testing competing theoriesfullstack-feature.mdFrontend/backend/tests coordinationarchitecture-decision.mdADR with adversarial debatebottleneck-analysis.mdCross-domain performance investigationinventory-classification.mdData-parallel classification/refactoring Each template includes: when to use, team structure, copy-paste spawn prompt, expected outcomes.
4. Spawn Team
claude --pty # Paste spawn prompt from template Monitor with ./scripts/team-monitor.sh (separate terminal) or Ctrl+T (in Claude Code).
Core Principles
Clear file boundaries - Each teammate owns different files/directories (prevents conflicts) Use delegate mode - Lead coordinates, teammates implement (include in spawn prompt) Size tasks appropriately - 5-6 self-contained tasks per teammate Wait for completion - Don't let lead merge results while teammates are mid-task Start with research - Spawn researchers before builders to establish shared understanding
Cost Management
Agent teams multiply token usage 3-4x vs single session. Each teammate has its own context window. Optimize with: Model mixing - Opus for lead (strategic), Sonnet for teammates (tactical) = ~40% savings Minimize broadcasts - Direct messages only (broadcasts copy to all teammates) Right-size teams - 3 teammates usually optimal; 6+ only for highly parallel work See references/cost-management.md for detailed strategies.
Troubleshooting
Teammates not spawning? Verify CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set Restart Claude Code after setting env var File conflicts? Define explicit file boundaries in spawn prompt (directory-level ownership) Lead implementing instead of coordinating? Add "Use delegate mode: coordinate but don't implement" to spawn prompt Or press Shift+Tab to cycle into delegate mode See references/troubleshooting.md for full list.
Automation
Monitor progress: ./scripts/team-monitor.sh Cleanup (graceful shutdown): ./scripts/team-cleanup.sh
Display Modes
In-process (default) - All teammates in main terminal Shift+Up/Down - Select teammate Ctrl+T - Toggle task list Escape - Interrupt teammate Split-pane (requires tmux or iTerm2) - Each teammate gets own pane Set teammateMode: "tmux" in ~/.claude/settings.json
References
templates/ - 6 copy-paste ready spawn prompts with usage guidance scripts/ - Automation helpers (validate, monitor, cleanup) references/best-practices.md - When to use teams, task sizing, file boundaries references/cost-management.md - Token optimization strategies references/troubleshooting.md - Common issues and solutions examples/ - Real-world walkthroughs (PR review, bug hunt, feature build)
Comparison
ApproachBest ForSingle sessionSequential work, explorationAgent teams (this skill)Parallel independent tasks with coordinationOpenClaw subagentsBackground work, long-running tasks
Contributing
Found a useful pattern? Submit PR with: Template or example When to use + team structure Spawn prompt + expected outcomes
Credits
Built with insights from Claude Code documentation, ClaudeFast patterns, and OpenClaw community. Repository: https://github.com/matthew-a-gordon/claude-code-teams License: MIT
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs2 Scripts1 Config
- SKILL.md
- README.md
- RESEARCH-SYNTHESIS.md
- scripts/team-cleanup.sh
- scripts/team-monitor.sh
- package.json