Agent skill

Team Agent Pipeline

Spawns a chosen number of coordinated agents on a shared task list and runs them through plan, requirements, execution, verification and fix stages.

MITAuto-check passedAgent Workflows

Install Team Agent Pipeline

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/team .claude/skills/team && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .claude/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/team .agents/skills/team && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .agents/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/team .cursor/skills/team && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .cursor/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/zereight/gitlab-mcp.git --path .github/skills/team

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/team .gemini/skills/team && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .gemini/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/team .github/skills/team && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .github/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add zereight/gitlab-mcp --skill team -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install zereight/gitlab-mcp team --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/team .opencode/skills/team && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "team" agent skill from https://github.com/zereight/gitlab-mcp/tree/main/.github/skills/team into .opencode/skills/team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "team", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: team
GitHub stars: 2k
Used in: 1 other repo
Token cost: ~1.5k tokens
SKILL.md length: 579 words
Files: 1
Skills in repo: 24
Repo updated: Oct 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Spawns a chosen number of coordinated agents on a shared task list and runs them through plan, requirements, execution, verification and fix stages.

Works in 8 steps: Parse Input → Analyze & Decompose → Create Team → …
Splitting a large refactor or migration across several parallel agents
SKILL.md covers When to Use, When NOT to Use, Usage and Architecture, plus 6 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

This skill starts several agents that work from one shared task list, using VS Code's native subagent system for team management, messaging between agents and task dependencies. You call it with a slash command such as /team 3:executor followed by the task, choosing how many agents to run (1 to 20, sized automatically if left out) and optionally which agent type handles the execution stage.

Work moves through a staged pipeline: team-plan, team-prd, team-exec, team-verify and a team-fix loop. A lead picks specialist agents for each stage, for example an explorer and planner for planning and a verifier for checks, and security-sensitive or very large changes must also get a security reviewer and a code reviewer. An optional ralph flag wraps the team in a retry loop with verification. The skill itself says to skip it for single-file edits and strictly sequential work.

When your agent uses it

Splitting a large refactor or migration across several parallel agents
Fixing a batch of TypeScript errors spread over many modules
Running multi-service work through plan, execute and verify stages
Adding a retry-until-verified loop around a decomposed task

Example prompts

“Spawn 3 executor agents to fix all TypeScript errors in the monorepo.”
“Start a team of 4 designers to implement responsive layouts across the dashboard pages.”
“Use a team to refactor the auth module, with verification before it reports done.”

Requirements

VS Code with its native subagent system

Workflow steps

8 steps, taken from the step headings in SKILL.md.

Parse Input
Analyze & Decompose
Create Team
Create Tasks
Spawn Workers
Monitor
Stage Transitions
Completion

What it can do on your machine

Read from SKILL.md and the folder at commit 0109168. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Team Agent Pipeline loads about 1.5k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 579 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~46
When it runs · the whole SKILL.md, loaded when a task matches: ~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zereight/gitlab-mcp at commit 0109168, republished under its MIT licence (© zereight). 579 words, ~1,508 tokens.

Download SKILL.mdSave it as .claude/skills/team/SKILL.md (or your agent's skills folder).

name: team
description: N coordinated agents on shared task list with staged pipeline. Activate when user says: team, spawn agents, parallel agents, coordinate agents, multi-agent, swarm, work together.
argument-hint: [N:agent-type] [ralph] <task description>

Team

Spawn N coordinated agents working on a shared task list. Uses VS Code's native subagent system for team management, inter-agent messaging, and task dependencies.

When to Use

Task is decomposable into independent subtasks
Multiple files/modules need parallel work
Large-scale refactoring, migration, or multi-service work

When NOT to Use

Single-file changes → use /omg-autopilot or direct editing
Sequential pipeline → use /omg-autopilot
Just need a plan → use /plan or /ralplan

Usage

/team 3:executor "fix all TypeScript errors"
/team 4:designer "implement responsive layouts"
/team "refactor the auth module"
/team ralph "build a complete REST API"

Parameters

N — Number of agents (1-20). Defaults to auto-sizing.
agent-type — Agent for team-exec stage (executor, debugger, designer, etc.). Defaults to stage-aware routing.
ralph — Wraps team in Ralph's persistence loop (retry on failure, verification before completion).
task — High-level task to decompose and distribute.

Architecture

User: "/team 3:executor fix all TypeScript errors"
              |
              v
      [omg-coordinator (Lead)]
              |
              +-- Analyze & decompose → subtask list
              |
              +-- Create tasks with dependencies
              |
              +-- Spawn N worker agents (subagents)
              |
              +-- Monitor loop (messages + task polling)
              |
              +-- Completion → shutdown workers → cleanup

Staged Pipeline

team-plan → team-prd → team-exec → team-verify → team-fix (loop)

Stage Agent Routing

Each stage uses specialized agents — not just executors:

Stage	Required Agents	Optional Agents
team-plan	@explore, @planner	@analyst, @architect
team-prd	@analyst	@critic
team-exec	@executor	@debugger, @designer, @writer, @test-engineer
team-verify	@verifier	@test-engineer, @security-reviewer, @code-reviewer
team-fix	@executor	@debugger

Routing rules:

Lead picks agents per stage, not the user. User's N:agent-type only overrides team-exec workers.
Specialist agents complement executors. Route analysis to @architect, UI to @designer.
Security-sensitive or >20 file changes must include @security-reviewer + @code-reviewer in team-verify.

Stage Entry/Exit Criteria

team-plan: Entry = invocation. Exit = task graph ready.
team-prd: Entry = scope ambiguous. Exit = acceptance criteria explicit.
team-exec: Entry = tasks created + workers spawned. Exit = tasks reach terminal state.
team-verify: Entry = execution pass done. Exit (pass) = gates pass. Exit (fail) = fix tasks generated.
team-fix: Entry = defects found. Exit = fixes done, return to team-verify.

Verify/Fix Loop

Continue team-exec → team-verify → team-fix until:

Verification passes with no required fixes, or
Max fix attempts exceeded (default: 3) → terminal failed

Workflow

Phase 1: Parse Input

Extract N (agent count, validate 1-20)
Extract agent-type
Extract task description
Check for ralph modifier

Phase 2: Analyze & Decompose

Use @explore or @architect to analyze the codebase and break the task into N subtasks:

Each subtask should be file-scoped or module-scoped
Subtasks must be independent or have clear dependencies
Each needs a concise subject and detailed description

Phase 3: Create Team

Write team state via omg_write_state:

json

{
  "mode": "team",
  "active": true,
  "team_name": "fix-ts-errors",
  "agent_count": 3,
  "current_phase": "team-plan",
  "task": "fix all TypeScript errors"
}

Show full SKILL.md (232 more words)Show less

Phase 4: Create Tasks

Create subtasks with dependencies. Pre-assign owners to avoid race conditions.

Phase 5: Spawn Workers

Spawn N subagents in parallel using the agents field references:

Each worker gets team preamble + assigned tasks
Workers execute independently and report back

Phase 6: Monitor

Monitor via two channels:

Inbound messages — workers report completion or need help
Task polling — check overall progress periodically

Coordination actions:

Unblock a worker with guidance
Reassign work if a worker finishes early
Handle failures — reassign or spawn replacement

Watchdog policy:

Task stuck >5 min without messages → send status check
No messages >10 min → reassign task
Worker fails 2+ tasks → stop assigning to it

Phase 7: Stage Transitions

Update state on every stage transition via omg_write_state.

Phase 8: Completion

Signal shutdown to all workers
Wait for responses (15s timeout)
Clean up team resources and state
Report summary

Stage Handoff Convention

Each stage produces a handoff document before transitioning:

markdown

## Handoff: <current-stage> → <next-stage>
- **Decided**: [key decisions]
- **Rejected**: [alternatives and why]
- **Risks**: [identified risks]
- **Files**: [key files modified]
- **Remaining**: [items for next stage]

Handoffs saved to .omc/handoffs/<stage-name>.md. Survive cancellation for resume.

Team + Ralph Composition

When ralph modifier is present:

Ralph creates PRD with stories
Each story executed as a team pipeline
Team verify/fix loop satisfies story acceptance criteria
Ralph verifies story completion
Next story begins

State Tracking

Track in .omc/state/team-state.json via omg_write_state/omg_read_state.

Resume and Cancel

Resume: Restart from last non-terminal stage using state + handoffs
Cancel: /cancel → graceful shutdown → cleanup → state preserved/cleared per policy

Files

Just SKILL.md in .github/skills/team of zereight/gitlab-mcp.

Open the folder on GitHubat commit 0109168

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in zereight/gitlab-mcp, which our catalogue first saw on October 7, 2026.

jmstar85/oh-my-githubcopilot.github/skills/team

Compare with similar skills

Team Agent Pipeline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Team Agent Pipeline compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Team Agent Pipeline this skillzereight/gitlab-mcp	2k	1 repos	~1.5k	Automated safety check: Pass	MIT	yesterday
OMA Multi-Agent Orchestratorfirst-fluke/oh-my-agent	1.3k	—	~3.1k	Automated safety check: Pass	MIT	yesterday
Swarm Parallel Dispatchlangchain-ai/langchain-skills	1.3k	—	~3k	Automated safety check: Pass	MIT	yesterday
Agents Project Coordinatorasgeirtj/system_prompts_leaks	69k	—	~2.9k	Automated safety check: Pass	CC0-1.0	yesterday
Cursor Orchestratecursor/plugins	10k	—	~1.1k	Automated safety check: Pass	None	today
Launching Agent Teamslexler/skill-factory	239	—	~1.3k	Automated safety check: Pass	Apache-2.0	1 mo ago

Similar skills

OMA Multi-Agent Orchestrator
first-fluke/oh-my-agent
Splits a complex feature into prioritized tasks, spawns specialist CLI subagents in parallel, tracks them through shared memory and verifies each result.
1.3k GitHub stars~3.1k tokensUpdated yesterday
Agent WorkflowsAuto-check passed
Swarm Parallel Dispatch
langchain-ai/langchain-skills
Official
Fans a list of independent items out to subagents in parallel, merges the results back into a table and supports retrying only the rows that failed.
1.3k GitHub stars~3k tokensUpdated yesterday
Agent WorkflowsAuto-check passed
Agents Project Coordinator
asgeirtj/system_prompts_leaks
Runs a goal as a project in which the agent coordinates separate agent threads, judging when to split the work, and interviews you first when nothing can be verified.
69k GitHub stars~2.9k tokensUpdated yesterday
Agent WorkflowsAuto-check passed
Cursor Orchestrate
cursor/plugins
Official
Splits a large goal into a tree of parallel Cursor cloud agents, with planners, workers and verifiers coordinated by a script and reporting through structured handoffs.
10k GitHub stars~1.1k tokensUpdated today
Agent WorkflowsAuto-check passed
Launching Agent Teams
lexler/skill-factory
Plans and launches Claude Code agent teams with distinct roles, right-sized tasks and detailed spawn prompts, and says when subagents or worktrees fit better.
239 GitHub stars~1.3k tokensUpdated 1 mo ago
Agent WorkflowsAuto-check passed
Agent Orchestrator
NeverSight/learn-skills.dev
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents.
216 GitHub starsUsed in 1 repo~1.4k tokens
Agent WorkflowsAuto-check passed

Questions about Team Agent Pipeline

What does Team Agent Pipeline do?

Spawns a chosen number of coordinated agents on a shared task list and runs them through plan, requirements, execution, verification and fix stages. This skill starts several agents that work from one shared task list, using VS Code's native subagent system for team management, messaging between agents and task dependencies. You call it with a slash command such as /team 3:executor followed by the task, choosing how many agents to run (1 to 20, sized automatically if left out) and optionally which agent type handles the execution stage.

When should I use Team Agent Pipeline?

Team Agent Pipeline fits situations like: splitting a large refactor or migration across several parallel agents; fixing a batch of TypeScript errors spread over many modules; running multi-service work through plan, execute and verify stages; adding a retry-until-verified loop around a decomposed task.

How do I install Team Agent Pipeline in Claude Code?

Run `npx skills add zereight/gitlab-mcp --skill team -a claude-code`. Or copy the skill folder (.github/skills/team in zereight/gitlab-mcp) into .claude/skills/team in your project. Claude Code loads it when a task matches its description.

How do I install Team Agent Pipeline in Codex?

Run `npx skills add zereight/gitlab-mcp --skill team -a codex`. Or copy the skill folder (.github/skills/team in zereight/gitlab-mcp) into .agents/skills/team in your project. Codex loads it when a task matches its description.

Can I use Team Agent Pipeline in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zereight/gitlab-mcp --skill team -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/team, .gemini/skills/team, .github/skills/team and .opencode/skills/team in your project.

What does Team Agent Pipeline need to run?

SKILL.md names no scripts, command-line tools or credentials: Team Agent Pipeline is instructions for the agent only. Our summary lists: VS Code with its native subagent system.

Does Team Agent Pipeline access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Team Agent Pipeline safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Team Agent Pipeline use?

Team Agent Pipeline is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Team Agent Pipeline use?

About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Team Agent Pipeline?

Skills that share tags, products or a category with Team Agent Pipeline: OMA Multi-Agent Orchestrator (first-fluke/oh-my-agent, 1.3k stars), Swarm Parallel Dispatch (langchain-ai/langchain-skills, 1.3k stars), Agents Project Coordinator (asgeirtj/system_prompts_leaks, 69k stars) and Cursor Orchestrate (cursor/plugins, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Team Agent Pipeline?

zereight (a GitHub user) maintains it in zereight/gitlab-mcp, which has 2,027 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 6, 2026.

Source: zereight/gitlab-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Team Agent Pipeline

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Team

When to Use

When NOT to Use

Usage

Parameters

Architecture

Staged Pipeline

Stage Agent Routing

Stage Entry/Exit Criteria

Verify/Fix Loop

Workflow

Phase 1: Parse Input

Phase 2: Analyze & Decompose

Phase 3: Create Team

Phase 4: Create Tasks

Phase 5: Spawn Workers

Phase 6: Monitor

Phase 7: Stage Transitions

Phase 8: Completion

Stage Handoff Convention

Team + Ralph Composition

State Tracking

Resume and Cancel

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from zereight/gitlab-mcp

Related

Questions about Team Agent Pipeline