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openclaw-team-builder-skillOpenClaw team 构建器技能

Agent Skill

openclaw-team-builder-skill 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

总安装

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周安装

316

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下载量

2,503
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:openclaw-team-builder-skill(OpenClaw team 构建器技能)
来源仓库:https://github.com/joeszeles/openclaw-team-builder-skill
安装命令:
openclaw skills install openclaw-team-builder-skill
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install openclaw-team-builder-skill

简介

openclaw-team-builder-skill 从专家名册组建激活团队。

  • 覆盖核心、部门与研究实验室三层结构。
  • 通过 clawhub 安装,使用 openclaw skills install 命令部署。
  • 安装前需确认权限范围、维护状态及是否触发人员调度操作。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
team-builder
description
Discover, compose, and activate specialist teams from 3 rosters — OpenClaw Core (CEO/IG/Artist), Agency Division (55+ specialists), and Research Lab (autonomous experiment loops). Planner proposes optimal teams; Reviewer validates deliverables.

Team Builder

Compose the right team for any job by drawing from three rosters of specialists. The Planner analyzes incoming work and proposes an optimal team; the Reviewer validates deliverables before sign-off.

Quick Start

  1. Receive a task — any job, project, or request
  2. Read PLANNER.md in this skill folder — follow the workflow to classify the domain and propose a team
  3. Activate specialists — load the relevant agent definition from the reference files listed below
  4. Execute — hand off work through the team using the handoff templates
  5. Review — read REVIEWER.md and run the QA workflow before final delivery

The Three Rosters

1. Core Team (TEAM-CORE.md)

The permanent OpenClaw agents. Always available, always running.

AgentRoleWorkspace
CEOLeader, orchestrator, final authority.openclaw/workspace/
IGTrading specialist, market operations.openclaw/workspace-ig/
ArtistImage generation, visual analysis.openclaw/workspace-artist/

2. Agency Division (TEAM-AGENCY.md)

55+ specialist agents across 9 divisions. Activated on demand from reference/agency-agents-main/.

DivisionAgentsKey Specialists
Engineering7Frontend Developer, Backend Architect, AI Engineer, DevOps
Design7UI Designer, UX Architect, Image Prompt Engineer
Marketing8Growth Hacker, Content Creator, Social Media
Product3Sprint Prioritizer, Trend Researcher, Feedback Synthesizer
Project Management5Senior PM, Studio Producer, Experiment Tracker
Testing7Evidence Collector, Reality Checker, API Tester
Support6Analytics Reporter, Finance Tracker, Legal Compliance
Spatial Computing6XR Architect, visionOS Engineer
Specialized7Agents Orchestrator, Data Analytics, LSP Engineer

3. Research Lab (TEAM-RESEARCH.md)

Autonomous experiment methodology adapted from Karpathy's autoresearch. Run iterative experiment loops on any measurable problem.

Applicable to: trading strategy optimization, image analysis pipelines, model tuning, data analysis, any domain with a measurable metric.

Cross-Team Workflows

The real power is mixing specialists across rosters. Here are proven combinations:

Trading Strategy Optimization

IG (market context) + Research Lab (experiment loop) + AI Engineer (model tuning)
→ IG provides live market data and strategy parameters
→ Research Lab runs 5-min experiment iterations on backtests
→ AI Engineer tunes neural network parameters
→ Reviewer validates with evidence before deploying to live

Visual Content Pipeline

Artist (image generation) + Image Prompt Engineer (prompt crafting) + Visual Storyteller (narrative)
→ Image Prompt Engineer crafts detailed, structured prompts
→ Artist generates via xAI grok-imagine-image-pro
→ Visual Storyteller evaluates narrative quality
→ Iterate until quality threshold met

Astronomy / Image Analysis

Artist (image capture/generation) + Research Lab (analysis loop) + AI Engineer (classification)
→ Artist handles image acquisition and enhancement
→ Research Lab runs iterative analysis (feature detection, classification)
→ AI Engineer builds/tunes detection models
→ Results feed back for next iteration

Dashboard / UI Feature Build

Senior PM (scope) + Frontend Developer (build) + Evidence Collector (QA) + Reality Checker (sign-off)
→ PM breaks spec into tasks with acceptance criteria
→ Frontend Developer implements mobile-first
→ Evidence Collector screenshots and validates each task
→ Reality Checker gives final production-readiness verdict

Full Product Launch

CEO (orchestrate) + Engineering (build) + Design (UX) + Marketing (launch) + Testing (validate)
→ CEO activates Planner to scope the project
→ Engineering + Design work in parallel (Dev↔QA loops)
→ Marketing prepares launch materials
→ Reviewer signs off before go-live

Activating a Specialist

To activate any Agency specialist, load their definition file:

Read the agent definition at:
reference/agency-agents-main/[division]/[agent-file].md

Then adopt that agent's:
- Identity and personality
- Core mission and rules
- Workflow process
- Success metrics

File paths follow the pattern:

  • reference/agency-agents-main/engineering/engineering-frontend-developer.md
  • reference/agency-agents-main/design/design-image-prompt-engineer.md
  • reference/agency-agents-main/testing/testing-evidence-collector.md

See TEAM-AGENCY.md for the complete index with all file paths.

Handoff Protocol

When passing work between specialists, use this template:

## Handoff
| Field | Value |
|-------|-------|
| From | [Agent Name] |
| To | [Agent Name] |
| Task | [What needs to be done] |
| Priority | [Critical / High / Medium / Low] |

## Context
- Current state: [What's been done]
- Relevant files: [File paths]
- Constraints: [Limits, requirements]

## Deliverable
- What is needed: [Specific output]
- Acceptance criteria:
  - [ ] [Criterion 1]
  - [ ] [Criterion 2]

## Quality
- Evidence required: [What proof of completion looks like]
- Reviewer: [Who validates this deliverable]

For complete handoff templates (QA pass/fail, escalation, phase gates), see: reference/agency-agents-main/strategy/coordination/handoff-templates.md

NEXUS Pipeline Modes

For larger projects, use the NEXUS pipeline from the Agency framework:

ModeScaleAgentsTimeline
MicroSingle task/fix5-101-5 days
SprintFeature or MVP15-252-6 weeks
FullComplete productAll12-24 weeks

Pipeline phases: Discover → Strategize → Scaffold → Build → Harden → Launch → Operate

Quality gates between every phase. Evidence required for all assessments.

For full NEXUS strategy: reference/agency-agents-main/strategy/nexus-strategy.md For activation prompts: reference/agency-agents-main/strategy/coordination/agent-activation-prompts.md For quickstart: reference/agency-agents-main/strategy/QUICKSTART.md

Reference Files in This Skill

FileContents
SKILL.mdThis file — overview and quick start
TEAM-CORE.mdCEO/IG/Artist trio — roles, routing, interactions
TEAM-AGENCY.mdAll 55+ Agency specialists indexed by division
TEAM-RESEARCH.mdAutonomous experiment methodology
PLANNER.mdJob analysis → team proposal workflow
REVIEWER.mdQA validation workflow with quality gates

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

82.2%
按下载量换算2,057

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

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该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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