By jsonlee12138
Orchestrate multi-agent AI teams for collaborative software development workflows: bootstrap projects, create and manage roles, decompose tasks, dispatch workers, inspect status, ensure QA processes, and recover sessions via CLI commands.
npx claudepluginhub jsonlee12138/agent-team --plugin agent-teamCompatibility shell for the legacy umbrella agent-team skill. Use only when older prompts still reference `agent-team`; route the request to the dedicated scenario skill instead of treating this file as the primary execution surface.
Use when users explicitly ask to brainstorm, shape requirements, compare approaches, or produce a planning/design document before implementation. Turn rough ideas into validated brainstorming/design docs through focused dialogue, role-based analysis, and explicit user approval. Do not trigger this skill for straightforward implementation requests that do not need dedicated design exploration.
Read-only catalog browsing skill for searching and viewing role catalog information. Use when the user wants to list, search, inspect, or review catalog repositories and statistics.
Session context cleanup and file re-anchoring strategy for controller and worker sessions. Use when the session is drifting, phases change, or resumed work needs index-first recovery from files.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Project bootstrap and migration entry for initializing agent-team in a repository or migrating legacy project state.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.
Read-only local role browsing skill for controller, worker, and human sessions. Use when the user wants to list available local roles without creating roles or managing repositories.
Create or update role-specific skill packages with deterministic files. Supports output to skills/ (open-source publishing) or .agent-team/teams/ (team use). Triggers: 创建角色, 新建 role, create role, 更新 role scope, edit role, update role, add role skill, 修改角色配置. Use when the user asks to create, update, or edit frontend/backend/product (or custom) role skills with auto-generated role fields, guided brainstorming fallback, and curated skills selection.
Role source management skill for finding, adding, listing, checking, updating, and removing role repositories. Use when the user is managing where roles come from rather than browsing the catalog.
Rule refresh skill for syncing built-in rule templates and generated rule artifacts. Use when the user asks to sync rules or fix rule drift.
Skill cache maintenance skill for checking, updating, and cleaning installed skill artifacts. Use when the user asks to inspect or refresh skill cache state.
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Read-only task inspection skill for controller, worker, and human sessions. Use when the user wants to view task status, inspect a task, or list tasks without changing lifecycle state.
Scenario-first task lifecycle entry for controller and human sessions. Use when the user asks to create, assign, complete, archive, or inspect task flow through `agent-team task` commands.
Decompose requirement, design, or brainstorming documents into reviewable task drafts with one function per task and one file per task, then create `agent-team` task packages only after explicit approval. Use when turning a document into tasks, splitting oversized tasks, validating task boundaries, or preparing approved task files for `agent-team task create`.
Acceptance-first TDD workflow for solo implementation work. Use when handling a coding change directly and you want to follow a disciplined sequence: read context, define acceptance criteria, write failing tests when feasible, implement, verify, and conclude with passed, failed, or skipped with reason.
Controller-side worker dispatch entry for opening workers, checking targeted worker status, and replying to workers with existing `agent-team worker` and `agent-team reply` commands.
Read-only worker inspection skill for controller and human sessions. Use when the user wants to view worker status without opening a worker or sending a reply.
Worker-first recovery entry for resuming the current assignment from file artifacts. Use when a worker needs to recover task context, continue work, or re-anchor after a pause.
Worker-first reporting entry for sending completion, blocker, or decision-needed messages back to main through `agent-team reply-main`.
Governance-only workflow plan entry for controller and human sessions. Use when the user asks to generate, approve, activate, or close workflow plans through `agent-team workflow plan`.
Multi-agent team orchestration for Claude Code. Set up parallel AI agent teams with file-based planning, progress tracking, and role-based collaboration.
Share bugs, ideas, or general feedback.
Reference skills for Claude Code Tasks and Agent Teams features
AI Agent Team Operating System for Claude Code — persistent team management, meetings, task wall, company loop engine, and real-time dashboard
Multi-agent team orchestration for parallel task execution, research, and implementation
Multi-agent orchestration for Claude Code. 12 specialized agents working in parallel — planning, building, reviewing, debugging. Plus a Hub for always-alive multi-project sessions controllable from Telegram or Slack.
Manus-style context engineering for Claude Code Agent Teams. Coordinate multiple agents with shared planning files, structured task assignment, and persistent memory. Based on planning-with-files methodology.