Spawn N coordinated agents working on a shared task list using Claude Code's native team tools. Replaces the legacy /swarm skill (SQLite-based) with built-in team management, inter-agent messaging, and task dependencies -- no external dependencies required.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionteamExecute the skills CLI command in your project's root directory to begin installation:
Fetches team from yeachan-heo/oh-my-claudecode and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate team. Access via /team in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Spawn N coordinated agents working on a shared task list using Claude Code's native team tools. Replaces the legacy /swarm skill (SQLite-based) with built-in team management, inter-agent messaging, and task dependencies -- no external dependencies required.
The swarm compatibility alias was removed in #1131.
/oh-my-claudecode:team N:agent-type "task description"
/oh-my-claudecode:team "task description"
/oh-my-claudecode:team ralph "task description"
team-exec stage (e.g., executor, debugger, designer, codex, gemini). Optional; defaults to stage-aware routing. Use codex to spawn Codex CLI workers or gemini for Gemini CLI workers (requires respective CLIs installed). See Stage Agent Routing below./team 5:executor "fix all TypeScript errors across the project"
/team 3:debugger "fix build errors in src/"
/team 4:designer "implement responsive layouts for all page components"
/team "refactor the auth module with security review"
/team ralph "build a complete REST API for user management"
# With Codex CLI workers (requires: npm install -g @openai/codex)
/team 2:codex "review architecture and suggest improvements"
# With Gemini CLI workers (requires: npm install -g @google/gemini-cli)
/team 2:gemini "redesign the UI components"
# Mixed: Codex for backend analysis, Gemini for frontend (use /ccg instead for this)
User: "/team 3:executor fix all TypeScript errors"
|
v
[TEAM ORCHESTRATOR (Lead)]
|
+-- TeamCreate("fix-ts-errors")
| -> lead becomes team-lead@fix-ts-errors
|
+-- Analyze & decompose task into subtasks
| -> explore/architect produces subtask list
|
+-- TaskCreate x N (one per subtask)
| -> tasks #1, #2, #3 with dependencies
|
+-- TaskUpdate x N (pre-assign owners)
| -> task #1 owner=worker-1, etc.
|
+-- Task(team_name="fix-ts-errors", name="worker-1") x 3
| -> spawns teammates into the team
|
+-- Monitor loop
| <- SendMessage from teammates (auto-delivered)
| -> TaskList polling for progress
| -> SendMessage to unblock/coordinate
|
+-- Completion
-> SendMessage(shutdown_request) to each teammate
<- SendMessage(shutdown_response, approve: true)
-> TeamDelete("fix-ts-errors")
-> rm .omc/state/team-state.json
Storage layout (managed by Claude Code):
~/.claude/
teams/fix-ts-errors/
config.json # Team metadata + members array
tasks/fix-ts-errors/
.lock # File lock for concurrent access
1.json # Subtask #1
2.json # Subtask #2 (may be internal)
3.json # Subtask #3
...
Team execution follows a staged pipeline:
team-plan -> team-prd -> team-exec -> team-verify -> team-fix (loop)
Each pipeline stage uses specialized agents -- not just executors. The lead selects agents based on the stage and task characteristics.
| Stage | Required Agents | Optional Agents | Selection Criteria |
|---|---|---|---|
| team-plan | explore (haiku), planner (opus) |
analyst (opus), architect (opus) |
Use analyst for unclear requirements. Use architect for systems with complex boundaries. |
| team-prd | analyst (opus) |
critic (opus) |
Use critic to challenge scope. |
| team-exec | executor (sonnet) |
executor (opus), debugger (sonnet), designer (sonnet), writer (haiku), test-engineer (sonnet) |
Match agent to subtask type. Use executor (model=opus) for complex autonomous work, designer for UI, debugger for compilation issues, writer for docs, test-engineer for test creation. |
| team-verify | verifier (sonnet) |
test-engineer (sonnet), security-reviewer (sonnet), code-reviewer (opus) |
Always run verifier. Add security-reviewer for auth/crypto changes. Add code-reviewer for >20 files or architectural changes. code-reviewer also covers style/formatting checks. |
| team-fix | executor (sonnet) |
debugger (sonnet), executor (opus) |
Use debugger for type/build errors and regression isolation. Use executor (model=opus) for complex multi-file fixes. |
Routing rules:
N:agent-type parameter only overrides the team-exec stage worker type. All other stages use stage-appropriate specialists.opus agents to sonnet, sonnet to haiku where quality permits. team-verify always uses at least sonnet.security-reviewer + code-reviewer (opus) in team-verify.explore scans codebase, planner creates task graph, optionally analyst/architect for complex tasks.analyst extracts requirements, optionally critic.TeamCreate, TaskCreate, assignment, and worker spawn are complete.verifier + task-appropriate reviewers (see routing table).team-fix.executor/debugger depending on defect type.team-exec then team-verify.Continue team-exec -> team-verify -> team-fix until:
team-fix is bounded by max attempts. If fix attempts exceed the configured limit, transition to terminal failed (no infinite loop).
When transitioning between stages, important context — decisions made, alternatives rejected, risks identified — lives only in the lead's conversation history. If the lead's context compacts or agents restart, this knowledge is lost.
Each completing stage MUST produce a handoff document before transitioning.
The lead writes handoffs to .omc/handoffs/<stage-name>.md.
## Handoff: <current-stage> → <next-stage>
- **Decided**: [key decisions made in this stage]
- **Rejected**: [alternatives considered and why they were rejected]
- **Risks**: [identified risks for the next stage]
- **Files**: [key files created or modified]
- **Remaining**: [items left for the next stage to handle]
.omc/handoffs/ for session resume. They are not deleted by TeamDelete.## Handoff: team-plan → team-exec
- **Decided**: Microservice architecture with 3 services (auth, api, worker). PostgreSQL for persistence. JWT for auth tokens.
- **Rejected**: Monolith (scaling concerns), MongoDB (team expertise is SQL), session cookies (API-first design).
- **Risks**: Worker service needs Redis for job queue — not yet provisioned. Auth service has no rate limiting in initial design.
- **Files**: DESIGN.md, TEST_STRATEGY.md
- **Remaining**: Database migration scripts, CI/CD pipeline config, Redis provisioning.
.omc/handoffs/ to recover stage transition context./oh-my-claudecode:cancel requests teammate shutdown, waits for responses (best effort), marks phase cancelled with active=false, captures cancellation metadata, then deletes team resources and clears/preserves Team state per policy. Handoff files in .omc/handoffs/ are preserved for potential resume.complete, failed, and cancelled.Use explore or architect (via MCP or agent) to analyze the codebase and break the task into N subtasks:
subject and detailed descriptionCall TeamCreate with a slug derived from the task:
{
"team_name": "fix-ts-errors",
"description": "Fix all TypeScript errors across the project"
}
Response:
{
"team_name": "fix-ts-errors",
"team_file_path": "~/.claude/teams/fix-ts-errors/config.json",
"lead_agent_id": "team-lead@fix-ts-errors"
}
The current session becomes the team lead (team-lead@fix-ts-errors).
Write OMC state using the state_write MCP tool for proper session-scoped persistence:
state_write(mode="team", active=true, current_phase="team-plan", state={
"team_name": "fix-ts-errors",
"agent_count": 3,
"agent_types": "executor",
"task": "fix all TypeScript errors",
"fix_loop_count": 0,
"max_fix_loops": 3,
"linked_ralph": false,
"stage_history": "team-plan"
})
Note: The MCP
state_writetool transports all values as strings. Consumers must coerceagent_count,fix_loop_count,max_fix_loopsto numbers andlinked_ralphto boolean when reading state.
State schema fields:
| Field | Type | Description |
|---|---|---|
active |
boolean | Whether team mode is active |
current_phase |
string | Current pipeline stage: team-plan, team-prd, team-exec, team-verify, team-fix |
team_name |
string | Slug name for the team |
agent_count |
number | Number of worker agents |
agent_types |
string | Comma-separated agent types used in team-exec |
task |
string | Original task description |
fix_loop_count |
number | Current fix iteration count |
max_fix_loops |
number | Maximum fix iterations before failing (default: 3) |
linked_ralph |
boolean | Whether team is linked to a ralph persistence loop |
stage_history |
string | Comma-separated list of stage transitions with timestamps |
Update state on every stage transition:
state_write(mode="team", current_phase="team-exec", state={
"stage_history": "team-plan:2026-02-07T12:00:00Z,team-prd:2026-02-07T12:01:00Z,team-exec:2026-02-07T12:02:00Z"
})
Read state for resume detection:
state_read(mode="team")
If active=true and current_phase is non-terminal, resume from the last incomplete stage instead of creating a new team.
Call TaskCreate for each subtask. Set dependencies with TaskUpdate using addBlockedBy.
// TaskCreate for subtask 1
{
"subject": "Fix type errors in src/auth/",
"description": "Fix all TypeScript errors in src/auth/login.ts, src/auth/session.ts, and src/auth/types.ts. Run tsc --noEmit to verify.",
"activeForm": "Fixing auth type errors"
}
Response stores a task file (e.g. 1.json):
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
jezweb/claude-skills
Registry listing for team matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in team — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
team fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend team for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
team reduced setup friction for our internal harness; good balance of opinion and flexibility.
team fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for team matched our evaluation — installs cleanly and behaves as described in the markdown.
team reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend team for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: team is focused, and the summary matches what you get after install.
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