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Agent Skill · 研究检索

weekly-prep-brief(每周准备简报)

weekly-prep-brief 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。

weekly-prep-brief 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,权限为需要联网;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 6,788。

总安装 20,909周安装 880GitHub Stars 11,732下载 7,322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:weekly-prep-brief(每周准备简报)
来源仓库:https://github.com/anthropics/knowledge-work-plugins
仓库路径:skills/weekly-prep-brief
安装命令:
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill weekly-prep-brief
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/anthropics/knowledge-work-plugins --skill weekly-prep-brief

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。

weekly-prep-brief 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态,注意是否触发联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/weekly-prep-brief

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/anthropics/knowledge-work-plugins --skill week…;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

weekly-prep-brief 怎么安装?

在终端执行 npx skills add https://github.com/anthropics/knowledge-work-plugins --skill weekly-prep-br…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

weekly-prep-brief 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。

weekly-prep-brief 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。

weekly-prep-brief 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。

weekly-prep-brief 用的人多吗?

公开数据是累计安装 20,909 次,近一周安装 880 次,下载 7,322 次,GitHub 11,732 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。

weekly-prep-brief 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。
  • 来源仓库有 11,732 星,维护活跃度相对可查。

先想清楚的地方

  • 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

  • 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
weekly-prep-brief

每周准备简报 · 本页

20,90911,732需要联网未明确有提醒

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

Weekly Prep Brief

Generate a single comprehensive weekly briefing that covers every external customer or prospect call in the next 7 days, with per-meeting account and contact research from Common Room.

Briefing Process

Step 1: Get the Week's External Meetings

Option A — Calendar connected: Use the ~~calendar connector to fetch all meetings scheduled in the next 7 days (or a user-specified range). Filter to keep only external meetings — those with attendees from outside your organization. Discard internal-only meetings, one-on-ones with colleagues, and recurring internal syncs.

Identify for each external meeting:

  • Company name
  • Meeting date and time
  • External attendee names and email addresses

Option B — No calendar connected: Ask the user: "To build your weekly prep brief, I'll need your upcoming external calls. Please list them: company name, date/time, and attendee names."

Accept freeform input and parse it into a structured list before proceeding.

Step 2: Confirm the Meeting List

Present the identified meetings to the user for confirmation before beginning research:

"Here are the external calls I found for this week. Let me know if anything's missing or should be excluded: - [Company] — [Day], [Time] — [Attendees] - ..."

This prevents wasted research on cancelled or incorrect meetings.

Step 3: Research Each Meeting

For each confirmed external meeting, run in parallel where possible:

  1. Account research — full account snapshot using the account-research skill
  2. Contact research — profile for each external attendee using the contact-research skill

Common Room data is the primary source. After CR research, run a quick recency check for each company — this is supplementary, not primary:

  • Search "[company name]" news scoped to the last 7 days
  • For executive attendees, search their name for recent public posts or interviews
  • Only include findings that are genuinely noteworthy (funding, leadership changes, major press). Don't pad the brief with generic news.

Depth calibration:

  • For high-priority accounts (large accounts, open opportunities, renewal risk), produce full depth research
  • For lower-priority or short meetings, produce abbreviated snapshots (3–4 bullets each)

Step 4: Synthesize the Weekly Brief

Compile all per-meeting research into a single structured document, sorted by meeting date/time.

Open with a brief week-level overview that flags:

  • Any accounts with urgent signals (at-risk, trial expiring, expansion opportunity)
  • Any meetings that need special preparation or executive involvement
  • Total external call count and estimated time commitment

Output Format

# Weekly Prep Brief — Week of [Date]

## Week Overview
[2–4 bullets: key themes, flagged priorities, call count]

---

## [Monday / Tuesday / etc.]

### [Company Name] — [Time]
**Attendees:** [Names and titles]
**Meeting type:** [Discovery / QBR / Renewal / Expansion / etc. — inferred if possible]

**Company Snapshot**
[4–5 bullets: account status, top signals, recent activity]

**Attendee Profiles**
- **[Name]** ([Title]): [2–3 bullets on their signals, persona, conversation angle]
- [Repeat per attendee]

**Top Signals This Week**
[2–3 most relevant signals for this specific call]

**This Week's News** [If notable news found]
[Only genuinely noteworthy findings — funding, leadership changes, major press]

**Recommended Objectives**
[1–2 sentences: what to accomplish in this meeting]

---

[Repeat per meeting, sorted by date/time]

When a Meeting Has Sparse Data

If Common Room returns limited data for a particular meeting's account or attendees, use a compressed format for that meeting instead of the full template:

### [Company Name] — [Time] ⚠️ Limited Data
**Attendees:** [Names and titles if known]
**Data available:** [What Common Room actually returned]

**Web Search Results**
[Findings from web search — company news, attendee LinkedIn profiles]

**Note:** Common Room has limited data on this account. The rep may want to check directly in CR or gather context from colleagues before this call.

Do not generate a full meeting prep section (company snapshot, signal highlights, talking points, recommended objectives) from sparse data. A short honest section is more useful than a fabricated full one.

Quality Standards

  • Keep each meeting section scannable — reps read these in the morning, often on mobile
  • Always sort by date/time ascending
  • Flag urgent situations prominently (risk, trial expiration, open opps) — don't bury them
  • If a meeting has very thin Common Room data, use the sparse-data format above — never fill the full template with guesses
  • Total brief should be readable in 10–15 minutes for a week with 4–6 meetings
  • Every fact must come from a tool call — no invented deal context, activity, or signals

Reference Files

  • references/briefing-guide.md — guidelines for structuring briefings, prioritization logic, and how to handle edge cases (cancelled meetings, new accounts with no data, etc.)

平台分布

Codex

35.52%
按下载量换算2,601

Claude

30.85%
按下载量换算2,259

Cursor

16.87%
按下载量换算1,235

Gemini CLI

8.49%
按下载量换算622

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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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