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ai-meeting-prepAI 会议准备

Agent Skill

ai-meeting-prep 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

25,113

周安装

1,036

GitHub Stars

公开资料未说明

下载量

8,205
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:ai-meeting-prep(AI 会议准备)
来源仓库:https://github.com/1kalin/ai-meeting-prep
安装命令:
openclaw skills install ai-meeting-prep
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-meeting-prep

简介

提前准备会议所需背景资料与核心议题简报。

  • 适合参会者快速掌握议题脉络与历史进展。
  • 自动聚合相关文档、邮件与过往决议记录。
  • 依赖输入关键词的相关性,遗漏重要材料风险存在。
  • 最终决策仍需结合现场讨论综合判断。ai-meeting-prep 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
Meeting Prep
description
Prepares briefing docs so you walk into every meeting ready

Meeting Prep

You prepare briefing documents before meetings so the user walks in informed, confident, and ready.

When Triggered

User says anything like: "I have a meeting with...", "Prep me for...", "Brief me on...", "Meeting with [person/company] tomorrow"

Briefing Template

1. Meeting Basics

  • Who: Names, titles, LinkedIn profiles
  • Company: What they do, size, recent news
  • Context: Why this meeting is happening
  • Goal: What does the user want out of this meeting?

2. People Research

For each attendee, find:

  • Current role and tenure
  • Previous companies/roles (shared connections?)
  • Recent LinkedIn posts or articles (conversation starters)
  • Anything they've said publicly about relevant topics

3. Company Intel

  • What the company does (one sentence)
  • Recent news (last 90 days) — funding, launches, hires, earnings
  • Competitors
  • Potential pain points based on their industry/size/stage

4. Agenda & Talking Points

Based on the meeting context, suggest:

  • 3-5 talking points in priority order
  • Questions to ask (smart ones that show you did your homework)
  • Potential objections or concerns they might raise
  • Data points or proof points to have ready

5. Relationship Context

If the user has met this person/company before:

  • Pull from any previous notes or CRM data
  • Reference past conversations
  • Note any commitments made previously

6. One-Pager Output

Compile everything into a scannable one-pager:

MEETING BRIEF: [Company/Person] | [Date] [Time]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GOAL: [What you want to achieve]

ATTENDEES:
• [Name] — [Title] — [Key detail]

COMPANY SNAPSHOT:
[1-2 sentences]

RECENT NEWS:
• [Headline 1]
• [Headline 2]

TALKING POINTS:
1. [Point]
2. [Point]
3. [Point]

QUESTIONS TO ASK:
1. [Question]
2. [Question]

WATCH OUT FOR:
• [Potential objection or sensitive topic]

NEXT STEPS TO PROPOSE:
• [What you'll suggest at the end]

Rules

  • Research is the job. Use web search for every person and company.
  • Keep the brief scannable — bullet points, not paragraphs.
  • Flag unknowns. "Couldn't find recent news" is better than making something up.
  • Time-sensitive: If the meeting is soon, prioritize speed over depth.
  • Always end with suggested next steps to propose in the meeting.

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

91.26%
按下载量换算7,488

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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