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Agent Skill · 研究检索

clawteam(clawteam 搜索)

clawteam 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。

clawteam 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 36,315。

总安装 1,947周安装 78GitHub Stars 11下载 630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:clawteam(clawteam 搜索)
来源仓库:https://github.com/akillness/oh-my-skills
仓库路径:skills/clawteam
安装命令:
npx skills add https://github.com/akillness/oh-my-skills --skill clawteam
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/akillness/oh-my-skills --skill clawteam

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。

用于查找、检索和筛选相关信息,支持任务导向搜索。适合定位 ClawTeam 运行时所需的算子包与模板。可管理 worker 启动、隔离与恢复流程。安装命令:npx skills add https://github.com/akillness/oh-my-skills --skill clawteam。

使用前建议确认是否处于 ClawTeam 运行环境。

来源仓库内路径:skills/clawteam

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/akillness/oh-my-skills --skill clawteam;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

clawteam 怎么安装?

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

clawteam 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。

clawteam 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/akillness/oh-my-skills --skill clawteam 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。

clawteam 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。

clawteam 用的人多吗?

公开数据是累计安装 1,947 次,近一周安装 78 次,下载 630 次,GitHub 11 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。

clawteam 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
clawteam

clawteam 搜索 · 本页

1,94711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

clawteam — ClawTeam runtime operator router

Use this skill when the real question is "which ClawTeam operator packet do I need right now?"

clawteam owns the ClawTeam-specific runtime surface:

  • team / task / inbox state
  • worker spawning through tmux or subprocess
  • workspace or git-worktree isolation
  • board visibility and recovery flows
  • template launches
  • provider / preset / profile setup tied to spawn behavior

It does not own generic multi-agent orchestration, board governance, or lightweight subtask fan-out.

Read these support docs before stretching the boundary:

When to use this skill

  • The user explicitly says clawteam or clearly wants ClawTeam's team/task/inbox/worktree runtime
  • A leader should coordinate named workers with explicit task ownership and message passing
  • The user wants ClawTeam board commands such as board attach, board live, or board serve
  • The user wants a built-in ClawTeam template launch
  • The real blocker is provider/model/profile setup *inside ClawTeam* before spawn
  • The workflow spans developer delivery, product/ops research, content operations, or game work and the chosen runtime is ClawTeam

When not to use this skill

  • Generic multi-agent implementation loop with planning + QA → jeo, omc, omx, or ohmg
  • Board/work queue control outside the ClawTeam runtime → vibe-kanban
  • Lightweight parallel subtasks with no team/task/inbox/worktree state → built-in delegation / subagents
  • Planning or decomposition → task-planning
  • Tool comparison or platform survey → survey

Instructions

Step 1: Start from the packet already in hand

Use references/intake-packets-and-route-outs.md.

Normalize the request into one packet first:

clawteam_packet:
  primary_packet: manual-team | template-launch | monitor-recover | profile-setup | route-out
  backend: tmux | subprocess | unknown
  audience: developer-workflow | product-ops | marketing-content | game-production | mixed
  current_pain: ownership-split | quick-start | stuck-runtime | provider-setup | wrong-tool
  confidence: high | medium | low

Choose one primary packet only:

  • manual-team — explicit team lifecycle, worker roles, tasks, inboxes, dependencies
  • template-launch — launch a prebuilt ClawTeam team and monitor it
  • monitor-recover — inspect a running/stuck team, board, inbox, tasks, workspaces, or lifecycle state
  • profile-setup — preset/profile/provider/model/runtime setup before spawn
  • route-out — the request is not really about ClawTeam's runtime

Rule: if the user really means “multiple agents” rather than “ClawTeam,” route out immediately.

Step 2: Verify the minimal runtime before giving deeper commands

Check what already works before assuming ClawTeam will smooth it over.

python3 --version
clawteam --help

tmux -V

# Replace with the agent CLI the user actually wants to run:
claude --version
codex --version

Rules:

  1. If the underlying agent CLI does not work by itself, do not pretend clawteam spawn will fix it.
  2. Prefer tmux for visible interactive workers and live operator control.
  3. Prefer subprocess only when headless/background execution is the real need.
  4. If provider/model customization is the blocker, choose profile-setup before large spawn examples.

Step 3: Return the smallest useful command packet

Packet A — manual-team

Use this when ownership and dependencies must stay explicit.

clawteam team spawn-team my-team -d "Build the auth module" -n leader
clawteam spawn tmux claude --team my-team --agent-name architect --task "Design the API schema"
clawteam spawn tmux codex --team my-team --agent-name tester --task "Write integration tests"
clawteam task create my-team "Design the API schema" -o architect
clawteam inbox send my-team tester "Wait for API handoff before final checks"
clawteam board attach my-team

Use references/use-cases.md if the user needs fuller examples for fullstack, research, content, or game-production splits.

Packet B — template-launch

Use this when a built-in template already matches the job.

clawteam template list
clawteam launch hedge-fund --team fund1 --goal "Analyze AAPL, MSFT, NVDA for Q2 2026"
clawteam board attach fund1

Do not bury this in a full manual-team walkthrough unless the template clearly fails to fit.

Packet C — monitor-recover

Use this when a team already exists or runtime truth is the real question.

clawteam team discover
clawteam team status my-team
clawteam board show my-team
clawteam task list my-team --status blocked
clawteam inbox peek my-team
clawteam workspace list my-team

Use this packet to inspect stuck workers, blocked tasks, missing inbox activity, or workspace drift.

Packet D — profile-setup

Use this when the runtime/provider setup is the actual blocker.

clawteam preset list
clawteam preset show moonshot-cn
clawteam preset generate-profile moonshot-cn claude --name claude-kimi
clawteam profile doctor claude
MOONSHOT_API_KEY=*** clawteam profile test claude-kimi
clawteam spawn tmux --profile claude-kimi --team my-team --agent-name researcher --task "Compare onboarding flows"

Use this packet before large team examples when the question is really about provider/model/runtime configuration.

Step 4: Keep the runtime reality honest

ClawTeam-style workflows are still operator-heavy.

State these realities when relevant:

  • tmux + worktree/session inspection is often part of the real workflow, not an implementation detail
  • long-running worker persistence may be fragile in some flows; do not oversell it
  • trust prompts, permission flows, and backend-specific quirks can still leak through the abstraction
  • manual cleanup, merge, or workspace hygiene may still matter after a run

Important upstream caveats:

  • issue #148 documents worker keepalive problems in ongoing-job subprocess patterns
  • issue #146 documents gaps between parsed agent definitions/configs and applied runtime behavior

If the user wants generic orchestration policy, board governance, or lightweight built-in delegation, route outward instead of growing this skill.

Step 5: Return one concise operator brief

Preferred format:

# ClawTeam Operator Brief

## Packet
- Packet:
- Why it fits:
- Backend:

## Preconditions
- Verified:
- Missing / risky:

## Commands
1. ...
2. ...
3. ...

## Monitoring / recovery
- ...

## Caveats
- ...

## Route-outs kept out of scope
- ...

Short, truthful packets beat giant command dumps.

Examples

Example 1: Fullstack feature split

Input

Use ClawTeam to split a full-stack feature across a leader and two workers.

Good output direction

  • choose manual-team
  • verify the runtime and worker CLI first
  • create the team, spawn workers, create explicit tasks, and end with a board command
  • keep planning/review policy outside this skill

Example 2: Template first

Input

Launch a built-in ClawTeam team and let me watch it.

Good output direction

  • choose template-launch
  • use template list if needed
  • use launch... --team... --goal...
  • monitor with board attach or board serve

Example 3: Runtime recovery

Input

A ClawTeam worker keeps dying after its first turn. What should I check?

Good output direction

  • choose monitor-recover
  • inspect team, board, task, inbox, and workspace state
  • mention that long-running worker persistence is not guaranteed in every flow
  • avoid pretending a generic orchestration skill owns the problem

Example 4: Honest route-out

Input

I just need a generic multi-agent implementation loop with planning and QA.

Good output direction

  • choose route-out
  • recommend jeo, omc, omx, or ohmg
  • explain that clawteam is the ClawTeam runtime/operator surface, not the generic answer to every multi-agent request

Best practices

  1. Pick one packet first instead of dumping every ClawTeam command family.
  2. Verify the underlying agent CLI and backend before spawning workers.
  3. Prefer tmux for visible operator control; use subprocess only when headless execution is the real need.
  4. Use template launch only when the built-in archetype actually fits.
  5. Treat provider/profile setup as its own path.
  6. Keep worker persistence and config-application caveats explicit.
  7. Keep clawteam distinct from orchestration routers, planning skills, and board-governance tools.
  8. Update compact and discovery surfaces when the trigger wording changes materially.

References

平台分布

Codex

35.33%
按下载量换算223

Claude

30.9%
按下载量换算195

Cursor

17.05%
按下载量换算107

Gemini CLI

8.66%
按下载量换算55

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

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/akillness/oh-my-skills --skill clawteam 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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