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Agent Skill · 研究检索

ensemble-team(合奏队)

ensemble-team 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ensemble-team 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 33,704。

总安装 2,321周安装 93GitHub Stars 2下载 751核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ensemble-team(合奏队)
来源仓库:https://github.com/jwilger/agent-skills
仓库路径:skills/ensemble-team
安装命令:
npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

搭建 AI 编程团队协作框架,支持单驾驶员 mob programming 模式。集成 TDD、持续回顾与共识决策机制,提升代码质量与开发效率。自动生成团队角色结构与工作流程文档,降低协作门槛。需明确技术栈与 MVP 范围,否则难以合理分配专家 agent 职责。

ensemble-team 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ensemble-team

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ensemble-team 怎么安装?

在终端执行 npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ensemble-team 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ensemble-team 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

ensemble-team 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ensemble-team 用的人多吗?

公开数据是累计安装 2,321 次,近一周安装 93 次,下载 751 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ensemble-team 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ensemble-team

合奏队 · 本页

2,3212执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Ensemble Team Setup

Set up an AI ensemble programming team for any software project. Creates the full structure for a team of expert agents working in a single-driver mob programming style with consensus-based decisions, TDD, and continuous retrospectives.

Workflow

Phase 1: Project Discovery

Gather essential project information. Ask the user:

  1. Project name and description: What is being built? What problem does it solve?
  2. Tech stack: Language, framework, database, frontend approach, testing tools. If unsure, help them decide based on their goals.
  3. Product vision: Target user? MVP scope? Vague ideas are fine — the Product Manager agent will refine them.
  4. Dev environment: Nix? Docker? Standard package managers? CI provider?
  5. Repository: Existing repo or new? Branching strategy?

Phase 2: Team Composition

Determine the right team.

PREREQUISITE: Read references/role-catalog.md before proceeding.

Tiered Team Presets

Start with a preset, then adjust based on project needs. The team formation session (Phase 5) helps determine the right fit. The user may modify any preset.

PresetSizeComposition
Full~91 Product Manager, 1 UI/UX Designer, 1 Accessibility Specialist, 1 Domain SME, 1 QA Analyst, 4 Software Engineers
Lean~5-61 Product Manager, 1 Domain SME, 1 Dev Practice Lead, 2-3 Software Engineers, 1 flex role (UX, QA, or DevOps based on need)
Solo-plus~31 Domain SME, 1 Dev Practice Lead, 1 Software Engineer

Approximate token costs per discussion round:

  • Solo-plus (~3 agents): Lightweight. ~5-10K tokens per round.
  • Lean (~5-6 agents): Moderate. ~15-25K tokens per round.
  • Full (~9 agents): Heavy. ~30-50K tokens per round. Reserve for projects where the governance overhead pays for itself.

Actual costs depend on model, context length, and discussion complexity. These are rough estimates for setting expectations, not precise accounting.

Selecting a preset: Ask the user about project scope, timeline, and complexity. Solo-plus suits focused tasks or spikes. Lean suits most projects. Full suits large-scope products with UI, accessibility, and quality requirements.

Extend, do not replace: These presets build on the role catalog. See the catalog for conditional roles (Security, Data/ML, API Specialist, etc.) that can augment any preset. Odd numbers preferred for tie-breaking.

Research each expert — do NOT pick from a memorized list. For each role:

  1. Identify the specific technology/domain this project needs
  2. Use WebSearch to find the recognized authority — the person who wrote the book, created the tool, or gave the defining talks for that specific area
  3. Verify their credentials, recent work, and relevance to this project
  4. Evaluate: published authority, distinctive voice, practical experience, complementary perspective to other team members

Present each proposed expert with: name, credentials, key published work, why they fit THIS project, and what they'd focus on. Let user approve, swap, or remove.

Phase 3: Generate Team Profiles

Create .claude/agents/<name>.md for each member.

PREREQUISITE: Read references/profile-template.md before proceeding.

Required sections: Opening bio, Role, Core Philosophy (5-8 principles from their published work), Technical Expertise (6-12 items), On This Project (concrete guidance), Communication Style (personality + 4-6 characteristic phrases), Mob Approach, Code Review Checklist (6-12 checks), Lessons (empty, to be updated).

Quality gates: Profile must not be interchangeable with another expert. Must include project-specific guidance. Must capture their distinctive voice.

AI-Approximation Disclaimer

Every profile MUST include the following disclaimer block immediately after the opening biography paragraph:

> **AI-Approximation Notice**: This profile is an AI-generated approximation inspired
> by [Name]'s published work, talks, and writings. The real [Name] has not endorsed
> or reviewed this profile. All outputs should be verified against their actual
> published work. This profile creates a "diversity of heuristics" drawing on their
> known perspectives — it does not simulate the actual person.
AI Self-Awareness Clause

Each profile must include in the "Your Role on This Team" section a statement that the team member is aware it is an AI agent embodying a perspective, not the actual person. Human time constraints are irrelevant to AI agents. Standing aside on a decision when the topic falls outside the role's expertise is appropriate deference, not disapproval.

Compressed Active-Context Form

Each profile MUST include a ## Compressed Context section at the end: a dense summary of the profile in under 500 tokens covering role, top 3-5 principles, key expertise areas, and characteristic review focus. This compressed form is loaded during discussion and review phases. The full profile is loaded only when the member is actively driving or navigating code.

Phase 4: Generate Project Scaffolding

Coordinator Instructions

PREREQUISITE: Read references/coordinator-template.md before proceeding.

Fill in roster, build tools, team size. Generate the coordinator instructions at .team/coordinator-instructions.md. Then add a pointer in the harness-specific config file (e.g., CLAUDE.md for Claude Code, .cursorrules for Cursor, project instructions for other harnesses) directing the main agent to read .team/coordinator-instructions.md. The coordinator instructions file is for the coordinator only.

AGENTS.md — Team Structure Section

Insert a "Team Structure" managed section into AGENTS.md noting:

  • Team member profiles are located in .claude/agents/
  • Project owner constraints are defined in PROJECT.md
  • Domain glossary is maintained at docs/glossary.md

This section provides orientation for all agents. The conventions section of AGENTS.md will be populated by the team during the formation session (Phase 5).

PROJECT.md

PREREQUISITE: Read references/project-template.md before proceeding.

Fill in tech stack, scope (Must/Should/Could/Out), dev mandates, environment.

Supporting docs
  • docs/glossary.md: Domain glossary skeleton (Core Types table, Actions table, Errors table, Type Design Principles)
  • docs/deferred-items.md: Tracker table (Item | Category | Source | Severity | Status)
  • docs/future-ideas.md: Parking lot for out-of-scope ideas

Phase 5: Team Formation Session

This is the critical phase. The team debates and reaches consensus on their working conventions, architectural decisions, and domain terminology.

How it works: The coordinator activates the full team, then presents each discussion topic one at a time. The team debates, proposes approaches, and reaches consensus using the Robert's Rules protocol. Outputs go to the appropriate location based on the type of decision:

  • Working conventions (collaboration norms, definition of done, code conventions, communication norms, mob model details, retrospective cadence, tooling conventions) are recorded in the conventions section of AGENTS.md.
  • Architectural decisions (principles, deployment strategy, state management, testing philosophy) are recorded as ADRs in docs/ARCHITECTURE.md.
  • Domain terminology (types, actions, errors, naming conventions) updates docs/glossary.md.

The 10 topics (non-exhaustive — team may add more):

  1. How do we decide what to build?
  2. How does the Driver-Reviewer mob model work?
  3. When is a piece of work "done"?
  4. What is our commit and integration pipeline?
  5. How do we resolve disagreements?
  6. What are our code conventions?
  7. When and how do we hold retrospectives?
  8. What are our architectural principles?
  9. How do we communicate as a team?
  10. What tooling and repository conventions do we follow?

Each topic includes the problem it addresses and sub-questions to guide discussion. The team's answers become their conventions and decisions — not pre-canned templates.

Phase 6: Configure Permissions

Grant team agents the permissions they need to do their work (file editing, shell access, etc.). How this is configured depends on the harness:

  • Claude Code: Create/update .claude/settings.json with "allow": ["Edit", "Write", "Bash(*)"]
  • Cursor/Windsurf: Configure tool permissions in the IDE settings
  • Other harnesses: Follow the harness documentation for agent permission grants

Reviewers need write access to .reviews/ only. See references/file-based-reviews.md for scoped permission configuration and the review file workflow.

Phase 7: Configure CI

Add paths-ignore rules to CI config for any harness-generated session or transcript directories (e.g., .claude-sessions/ for Claude Code) to prevent them from triggering CI runs.

Phase 8: Summary

Present: files created, how to start the team. The harness config file (e.g., CLAUDE.md for Claude Code) references AGENTS.md via @ (or equivalent include mechanism), and the coordinator reads .team/coordinator-instructions.md for its operating instructions. Suggest telling the coordinator what to build.

Files created:

  • .claude/agents/<name>.md — agent definition files (team member profiles)
  • .team/coordinator-instructions.md — coordinator operating instructions
  • AGENTS.md — team structure and conventions (populated during formation session)
  • PROJECT.md — project owner constraints
  • docs/ARCHITECTURE.md — architectural decision records (populated during formation session)
  • docs/glossary.md — domain glossary
  • docs/deferred-items.md — deferred items tracker
  • docs/future-ideas.md — parking lot for out-of-scope ideas
  • .reviews/ — review feedback directory (created by Reviewers during work)
  • Harness config pointer (e.g., CLAUDE.md) — directs coordinator to read .team/coordinator-instructions.md

Retrospective Protocol

A single agent writing all perspectives is NOT a retrospective — it is a summary. Every agent spawned for a retrospective MUST be a named team member from .claude/agents/.

Retrospectives are event-driven, not time-based. Trigger: after each shipped PR (merged to the integration branch).

See references/retrospective-protocol.md for the full procedure. The four mandatory phases:

  1. Previous Action Item Audit — Status all prior action items. Items marked NOT-STARTED from 2+ retros ago escalate to blocking.
  2. Individual Observations — Each member writes independently (to .reviews/retro/ files). No discussion until all have written.
  3. Team Discussion — Actual message exchange where members react to each other's observations. The coordinator verifies real exchange occurred (not a single agent summarizing).
  4. Consensus and Record — Consent protocol for proposals. Output to AGENTS.md conventions or ADRs. Every action item has a named owner.

Action item implementation gate: Retro action items are implemented before the next work item starts. This prevents the backlog of unaddressed improvements that makes retros feel pointless.

Mini-retros after each CI build remain a lightweight observational checkpoint (did we follow the pipeline? was the commit atomic?) and do not require human consent. They are observational, not prescriptive.

Key Principles

Non-negotiable aspects baked in from production experience.

PREREQUISITE: Read references/lessons-learned.md before proceeding.

  • Named team members only: every agent spawned for team work MUST be a named member from .claude/agents/. Never use generic background agents for team activities.
  • Consensus before push (review locally, then push)
  • Refactor step is mandatory every commit
  • CI wait rule (never queue multiple CI runs)
  • Mini-retro after every CI build (team runs it, not coordinator)
  • PR-triggered retrospective with consent-based outputs
  • Retro action items implemented before next work item starts
  • Driver handoff protocol (summary + git log + green baseline)
  • Glossary compliance (domain types match glossary)
  • Deferred items tracked immediately
  • Reviewer coordination (check others' reviews first)
  • Non-blocking feedback escalation: items appearing in 2+ consecutive reviews escalate to blocking
  • Explicit Driver onboarding in activation prompts
  • Session transcripts excluded from CI triggers
  • AI-approximation disclaimer on every profile
  • Compressed active-context form on every profile
  • Stand-aside means deference, not disapproval
  • File-based reviews survive context compaction (messaging supplements, not replaces)

Enforcement Note

  • Subagent mode: Structural. Named agent profiles enforce persona boundaries.
  • Chaining mode: Advisory. Self-enforced role switching.
  • Pipeline mode: Gating. Consensus gates block pipeline progression at defined checkpoints.

Constraints

  • AI disclaimer: The disclaimer must be substantively honest, not just formally present. Including the disclaimer text while writing the profile in a tone that implies real endorsement violates the spirit. The profile should read as "here is how an AI might approximate this person's perspective" not "here is what this person thinks."
  • "Named members only for team activities": Team activities include: retrospectives, consensus rounds, code reviews, and any task where the team member's perspective (not just their labor) matters. Background research, file manipulation, and mechanical tasks do not require named members.

See CONSTRAINT-RESOLUTION.md in the template directory for factory-mode consensus resolution.

Factory Mode (Optional)

When the pipeline skill is installed alongside ensemble-team, the coordinator detects this during setup and enables factory mode. This adds a Phase 1.5 ("Factory Mode Configuration") between team formation and the build phase.

In factory mode, the coordinator delegates the entire build phase to the pipeline controller rather than managing it directly. The pipeline handles slice queuing, TDD pair dispatch, code review orchestration, and merge decisions through quality gates. The full team still reviews before any push.

See references/factory-mode.md for coordinator handoff details.

Factory Mode vs. Supervised Mode

  • Supervised mode (default): The coordinator manages the build phase. All decisions use the Robert's Rules consensus protocol. The coordinator facilitates driver rotation, review cycles, and retrospectives.
  • Factory mode (when pipeline is installed): The pipeline manages the build phase. Quality gates replace consensus for build-time decisions. The coordinator remains active for planning, factory configuration, and post-build review. The full team participates in pre-push review and retrospectives as before.

平台分布

Codex

34.42%
按下载量换算258

Claude

26.84%
按下载量换算202

Cursor

19.61%
按下载量换算147

Gemini CLI

10.29%
按下载量换算77

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jwilger/agent-skills --skill ensemble-team 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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