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Agent Skill · 研究检索

oc-team-builder(OC 团队建设者)

oc-team-builder 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。

oc-team-builder 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,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 16,259。

总安装 7,296周安装 301GitHub Stars 公开资料未说明下载 2,384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
MIT-0
版本
2.0.0

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:oc-team-builder(OC 团队建设者)
来源仓库:https://github.com/joeszeles/oc-team-builder
安装命令:
openclaw skills install oc-team-builder
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 oc-team-builder

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。

从 OpenClaw 核心、代理部门和研究实验室中组建专家团队。适合根据关键词或任务需求快速匹配并激活对应领域专家。安装后输入场景描述即可获取候选名单及专长摘要。结果依赖内部名册数据,实际可用性需人工确认。oc-team-builder 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

不涉及敏感信息处理,但输出内容应作为参考而非最终决策。

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 OpenClaw;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 openclaw skills install oc-team-builder;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

    它需要需要联网,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

oc-team-builder 怎么安装?

在终端执行 openclaw skills install oc-team-builder。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

oc-team-builder 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

oc-team-builder 需要什么权限?

权限级别是需要联网。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。

oc-team-builder 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

oc-team-builder 用的人多吗?

公开数据是累计安装 7,296 次,近一周安装 301 次,下载 2,384 次。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。

oc-team-builder 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 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 OpenClaw,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

  • 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
oc-team-builder

OC 团队建设者 · 本页

7,296—需要联网MIT-0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

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

Team Builder

Compose the right team for any job by drawing from three rosters of specialists. The Research Lab uses Karpathy's autoresearch methodology for autonomous experiment loops.

Quick Start — Scripts

1. Browse available agents

bash {baseDir}/scripts/roster.sh                     # all 3 rosters
bash {baseDir}/scripts/roster.sh -r agency            # agency only
bash {baseDir}/scripts/roster.sh -d engineering        # one division
bash {baseDir}/scripts/roster.sh -s "frontend"         # search
bash {baseDir}/scripts/roster.sh -v                    # verbose descriptions
bash {baseDir}/scripts/roster.sh -j                    # JSON output

2. Generate a team proposal

bash {baseDir}/scripts/plan.sh "Build a portfolio dashboard with pie charts"
bash {baseDir}/scripts/plan.sh --mode sprint "Optimize image generation prompts using autoresearch"
bash {baseDir}/scripts/plan.sh -o proposal.md "Analyze astronomy photos for star classification"

The planner auto-detects task domains (engineering, creative, research, marketing, operations, spatial) and proposes the right-sized team (micro/sprint/full).

3. Activate a specialist

bash {baseDir}/scripts/activate.sh --division engineering --agent frontend-developer
bash {baseDir}/scripts/activate.sh --division testing --agent evidence-collector
bash {baseDir}/scripts/activate.sh --division testing --list
bash {baseDir}/scripts/activate.sh --file reference/agency-agents-main/design/design-ui-designer.md
bash {baseDir}/scripts/activate.sh --division engineering --agent ai-engineer --personality-only

Outputs the agent's full personality definition for use in delegation prompts.

4. Run QA review

bash {baseDir}/scripts/review.sh --task "Portfolio dashboard"
bash {baseDir}/scripts/review.sh --task "Image pipeline" --criteria criteria.txt --pass evidence
bash {baseDir}/scripts/review.sh --task "LLM training optimization" --pass reality
bash {baseDir}/scripts/review.sh --task "Full product" --pass both -o review.md

Generates review checklists (Evidence Collector Pass 1 + Reality Checker Pass 2) and logs to ~/.openclaw/team-reviews/.

5. Run a Research Lab experiment

bash {baseDir}/scripts/experiment.sh --setup /path/to/project     # initialize experiment
bash {baseDir}/scripts/experiment.sh --run /path/to/project       # run one experiment cycle
bash {baseDir}/scripts/experiment.sh --status /path/to/project    # show ledger

See references/TEAM-RESEARCH.md for the full autoresearch methodology and working examples.

The Three Rosters

1. Core Team (references/TEAM-CORE.md)

The permanent OpenClaw agents. Always available, always running.

AgentRoleWorkspace
CEOLeader, orchestrator, final authority.openclaw/workspace/
ArtistImage generation, visual analysis.openclaw/workspace-artist/

2. Agency Division (references/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 (references/TEAM-RESEARCH.md)

Autonomous experiment loops adapted from Karpathy's autoresearch. Set up a measurable experiment, run it in a fixed time budget, keep improvements, discard failures, loop forever.

Source code reference: reference/autoresearch-master/ (program.md, train.py, prepare.py)

Cross-Team Workflow Examples

Image Analysis + Research Loop

Artist (image acquisition) + Research Lab (analysis loop) + AI Engineer (classification)

Visual Content Pipeline

Artist (generation) + Image Prompt Engineer (prompts) + Visual Storyteller (narrative)

Dashboard / UI Feature Build

Senior PM (scope) + Frontend Developer (build) + Evidence Collector (QA)

Autonomous LLM Training (autoresearch)

Research Lab (experiment loop on train.py) + AI Engineer (architecture suggestions)
→ 12 experiments/hour, ~100 overnight, fully autonomous

Full Product Launch

CEO (orchestrate) + Engineering (build) + Design (UX) + Marketing (launch) + Testing (validate)

Handoff Protocol

When passing work between specialists:

## 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]

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

## Quality
- Evidence required: [What proof looks like]
- Reviewer: [Who validates]

For complete handoff templates: reference/agency-agents-main/strategy/coordination/handoff-templates.md

NEXUS Pipeline Modes

ModeScaleAgentsTimeline
MicroSingle task/fix1-3Hours-days
SprintFeature or MVP5-101-2 weeks
FullComplete product10+Weeks-months

Reference Files

FileContents
SKILL.mdThis file — overview, scripts, quick start
scripts/roster.shBrowse and search all agent rosters
scripts/plan.shGenerate team proposals from task descriptions
scripts/activate.shLoad agent personality definitions
scripts/review.shGenerate QA review checklists
scripts/experiment.shRun autoresearch experiment loops
references/TEAM-CORE.mdCEO/Artist — roles and interactions
references/TEAM-AGENCY.mdAll 55+ Agency specialists indexed by division
references/TEAM-RESEARCH.mdAutonomous experiment methodology (autoresearch)
references/PLANNER.mdJob analysis → team proposal workflow (detailed)
references/REVIEWER.mdQA validation workflow with quality gates
references/PROOF-OF-WORK.mdExample proposals showing cross-roster teams

平台分布

OpenClaw

75.57%
按下载量换算1,802

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

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

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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