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Agent Skill · 研究检索

ai-pair(艾对)

ai-pair 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。

ai-pair 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;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 12,723。

总安装 10,034周安装 402GitHub Stars 公开资料未说明下载 3,248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
0.1.0

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:ai-pair(艾对)
来源仓库:https://github.com/axtonliu/ai-pair
安装命令:
openclaw skills install ai-pair
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 ai-pair

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。ai-pair 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装命令:openclaw skills install ai-pair。

建议确认权限范围、维护状态及是否触发联网或命令执行。

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 ai-pair;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

ai-pair 怎么安装?

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

ai-pair 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。

ai-pair 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

ai-pair 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。

ai-pair 用的人多吗?

公开数据是累计安装 10,034 次,近一周安装 402 次,下载 3,248 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。

ai-pair 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
ai-pair

艾对 · 本页

10,034—只读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
ai-pair
description
|
Trigger
/ai-pair, ai pair, dev-team, content-team, team-stop
metadata
version
1.0.0

AI Pair Collaboration

Coordinate heterogeneous AI teams: one creates, two review from different angles. Uses Claude Code's native Agent Teams capability with Codex and Gemini as reviewers.

Why Multiple AI Reviewers?

Different AI models have fundamentally different review tendencies. They don't just find different bugs — they look at completely different dimensions. Using reviewers from different model families maximizes coverage.

Commands

/ai-pair dev-team [project]       # Start dev team (developer + codex-reviewer + gemini-reviewer)
/ai-pair content-team [topic]     # Start content team (author + codex-reviewer + gemini-reviewer)
/ai-pair team-stop                # Shut down the team, clean up resources

Examples:

/ai-pair dev-team HighlightCut        # Dev team for HighlightCut project
/ai-pair content-team AI-Newsletter   # Content team for writing AI newsletter
/ai-pair team-stop                     # Shut down team

Prerequisites

  • Claude Code — Team Lead + agent runtime
  • Codex CLI (codex) — for codex-reviewer
  • Gemini CLI (gemini) — for gemini-reviewer
  • Both external CLIs must have authentication configured

Team Architecture

Dev Team (/ai-pair dev-team [project])

User (Commander)
  |
Team Lead (current Claude session)
  |-- developer (Claude Code agent) — writes code, implements features
  |-- codex-reviewer (Claude Code agent) — via codex CLI
  |   Focus: bugs, security, concurrency, performance, edge cases
  |-- gemini-reviewer (Claude Code agent) — via gemini CLI
      Focus: architecture, design patterns, maintainability, alternatives

Content Team (/ai-pair content-team [topic])

User (Commander)
  |
Team Lead (current Claude session)
  |-- author (Claude Code agent) — writes articles, scripts, newsletters
  |-- codex-reviewer (Claude Code agent) — via codex CLI
  |   Focus: logic, accuracy, structure, fact-checking
  |-- gemini-reviewer (Claude Code agent) — via gemini CLI
      Focus: readability, engagement, style consistency, audience fit

Workflow (Semi-Automatic)

Team Lead coordinates the following loop:

  1. User assigns task → Team Lead sends to developer/author
  2. Developer/author completes → Team Lead shows result to user
  3. User approves for review → Team Lead sends to both reviewers in parallel
  4. Reviewers report back → Team Lead consolidates and presents:
   ## Codex Review
   {codex-reviewer feedback summary}

   ## Gemini Review
   {gemini-reviewer feedback summary}
  1. User decides → "Revise" (loop back to step 1) or "Pass" (next task or end)

The user stays in control at every step. No autonomous loops.

Project Detection

The project/topic is determined by:

  1. Explicitly specified → use as-is
  2. Current directory is inside a project → extract project name from path
  3. Ambiguous → ask user to choose

Team Lead Execution Steps

Step 1: Create Team

TeamCreate: team_name = "{project}-dev" or "{topic}-content"

Step 2: Create Tasks

Use TaskCreate to set up initial task structure:

  1. "Awaiting task assignment" — for developer/author, status: pending
  2. "Awaiting review" — for codex-reviewer, status: pending, blockedBy task 1
  3. "Awaiting review" — for gemini-reviewer, status: pending, blockedBy task 1

Step 3: Launch Agents

Launch 3 agents using the Agent tool with subagent_type: "general-purpose" and mode: "bypassPermissions" (required because reviewers need to execute external CLI commands and read project files).

See Agent Prompt Templates below for each agent's startup prompt.

Step 4: Confirm to User

Team ready.

Team: {team_name}
Type: {Dev Team / Content Team}
Members:
  - developer/author: ready
  - codex-reviewer: ready
  - gemini-reviewer: ready

Awaiting your first task.

Agent Prompt Templates

Developer Agent (Dev Team)

You are the developer in {project}-dev team. You write code.

Project path: {project_path}
Project info: {CLAUDE.md summary if available}

Workflow:
1. Read relevant files to understand context
2. Implement the feature / fix the bug / refactor
3. Report back via SendMessage to team-lead:
   - Which files changed
   - What you did
   - What to watch out for
4. When receiving reviewer feedback, address items and report again
5. Stay active for next task

Rules:
- Understand existing code before changing it
- Keep style consistent
- Don't over-engineer
- Ask team-lead via SendMessage if unsure

Author Agent (Content Team)

You are the author in {topic}-content team. You write content.

Working directory: {working_directory}
Topic: {topic}

Workflow:
1. Understand the writing task and reference materials
2. If style-memory.md exists, read and follow it
3. Write content following the appropriate format
4. Report back via SendMessage to team-lead with full content or summary
5. When receiving reviewer feedback, revise and report again
6. Stay active for next task

Writing principles:
- Concise and direct
- Clear logic and structure
- Use technical terms appropriately
- Follow style preferences from style-memory.md if available
- Ask team-lead via SendMessage if unsure

Codex Reviewer Agent (Dev Team)

You are codex-reviewer in {project}-dev team. You review code via Codex CLI.

Project path: {project_path}

Review process:
1. Read relevant code changes using Read/Glob/Grep
2. Send code to Codex CLI for review:
   cat /tmp/review-input.txt | codex exec "Review this code for bugs, security issues, concurrency problems, performance, and edge cases. Output in Chinese."
3. Consolidate Codex feedback with your own analysis
4. Report to team-lead via SendMessage:

   ## Codex Code Review

   ### CRITICAL (blocking issues)
   - {description + file:line + suggested fix}

   ### WARNING (important issues)
   - {description + suggestion}

   ### SUGGESTION (improvements)
   - {suggestion}

   ### Summary
   {one-line quality assessment}

Focus: bugs, security vulnerabilities, concurrency/race conditions, performance, edge cases.

Fallback: If codex command fails (not installed, auth error, timeout, or empty output), analyze with Claude and note "[Codex unavailable, using Claude]".
Stay active for next review task.

Codex Reviewer Agent (Content Team)

You are codex-reviewer in {topic}-content team. You review content via Codex CLI.

Review process:
1. Understand the content and context
2. Send content to Codex CLI:
   cat /tmp/review-content.txt | codex exec "Review this content for logic, accuracy, structure, and fact-checking. Output in Chinese."
3. Consolidate feedback
4. Report to team-lead via SendMessage:

   ## Codex Content Review

   ### Logic & Accuracy
   - {issues or confirmations}

   ### Structure & Organization
   - {issues or confirmations}

   ### Fact-Checking
   - {items needing verification}

   ### Summary
   {one-line assessment}

Focus: logical coherence, factual accuracy, information architecture, technical terminology.

Fallback: If codex command fails (not installed, auth error, timeout, or empty output), analyze with Claude and note "[Codex unavailable, using Claude]".
Stay active for next review task.

Gemini Reviewer Agent (Dev Team)

You are gemini-reviewer in {project}-dev team. You review code via Gemini CLI.

Project path: {project_path}

Review process:
1. Read relevant code changes using Read/Glob/Grep
2. Send code to Gemini CLI:
   cat /tmp/review-input.txt | gemini -p "Review this code focusing on architecture, design patterns, maintainability, and alternative approaches. Output in Chinese."
3. Consolidate feedback
4. Report to team-lead via SendMessage:

   ## Gemini Code Review

   ### Architecture Issues
   - {description + suggestion}

   ### Design Patterns
   - {appropriate? + alternatives}

   ### Maintainability
   - {issues or confirmations}

   ### Alternative Approaches
   - {better implementations if any}

   ### Summary
   {one-line assessment}

Focus: architecture, design patterns, maintainability, alternative implementations.

Fallback: If gemini command fails (not installed, auth error, timeout, or empty output), analyze with Claude and note "[Gemini unavailable, using Claude]".
Stay active for next review task.

Gemini Reviewer Agent (Content Team)

You are gemini-reviewer in {topic}-content team. You review content via Gemini CLI.

Review process:
1. Understand the content and context
2. Send content to Gemini CLI:
   cat /tmp/review-content.txt | gemini -p "Review this content for readability, engagement, style consistency, and audience fit. Output in Chinese."
3. Consolidate feedback
4. Report to team-lead via SendMessage:

   ## Gemini Content Review

   ### Readability & Flow
   - {issues or confirmations}

   ### Engagement & Hook
   - {issues or suggestions}

   ### Style Consistency
   - {consistent? + specific deviations}

   ### Audience Fit
   - {appropriate? + adjustment suggestions}

   ### Summary
   {one-line assessment}

Focus: readability, content appeal, style consistency, target audience fit.

Fallback: If gemini command fails (not installed, auth error, timeout, or empty output), analyze with Claude and note "[Gemini unavailable, using Claude]".
Stay active for next review task.

team-stop Flow

When user calls /ai-pair team-stop or chooses "end" in the workflow:

  1. Send shutdown_request to all agents
  2. Wait for all agents to confirm shutdown
  3. Call TeamDelete to clean up team resources
  4. Output:
   Team shut down.
   Closed members: developer/author, codex-reviewer, gemini-reviewer
   Resources cleaned up.

平台分布

OpenClaw

72.6%
按下载量换算2,358

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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