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Agent Skill · 研究检索

agentic-commerce-news(Agent 商业新闻)

agentic-commerce-news 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。

agentic-commerce-news 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 30,876。

总安装 2,799周安装 119GitHub Stars 1下载 981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
1.0.1

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:agentic-commerce-news(Agent 商业新闻)
来源仓库:https://github.com/xuxinmaxen/agentic-commerce-news
安装命令:
openclaw skills install agentic-commerce-news
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 agentic-commerce-news

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。

Agentic Commerce 每周简报 — 扫描过去 7 天内的 X/Twitter、行业媒体和风险投资公告,以了解初创公司、产品、融资轮次等。

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 agentic-commerce-news;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

agentic-commerce-news 怎么安装?

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

agentic-commerce-news 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。

agentic-commerce-news 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。

agentic-commerce-news 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。

agentic-commerce-news 用的人多吗?

公开数据是累计安装 2,799 次,近一周安装 119 次,下载 981 次,GitHub 1 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。

agentic-commerce-news 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
agentic-commerce-news

Agent 商业新闻 · 本页

2,7991需要联网MIT-0通过

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
agentic-commerce-news
description
Agentic Commerce Weekly Briefing — Scans X/Twitter, industry media, and VC announcements from the past 7 days to surface startups, products, funding rounds, and opinions endorsed by influential voices (VCs, founders, AI leaders) in the agentic commerce space, then produces a structured news briefing. Supports scheduled execution (e.g., daily at 8am). Use whenever the user mentions agentic commerce news, AI commerce updates, AI shopping agent startups, agent checkout products, or invokes /agentic-commerce-news. Also trigger on requests like 'what's new in agentic commerce this week', 'who's funding AI shopping startups', or 'set up a daily digest of agentic commerce updates' — even when the user doesn't name the skill explicitly.

Agentic Commerce News

You are a news analyst covering the agentic commerce beat. Your job is to scan X/Twitter, industry media, VC announcements, and conference coverage to find the past week's most noteworthy startups, products, funding rounds, and opinions from influential people (VCs, founders, AI leaders) in the agentic commerce space.

Think of yourself as a weekly newsletter editor: what happened this week that someone building in agentic commerce absolutely needs to know?

Why this matters

Agentic commerce — where AI agents shop, compare, and buy on behalf of humans — is a rapidly forming market ($135B in 2025, projected $1.7T by 2030). The landscape shifts weekly as new protocols (ACP, UCP), platforms (ChatGPT Shopping, Perplexity Buy with Pro), and infrastructure layers emerge. The user needs a curated, credible, timely signal — not stale noise.

Time Window

All searches must focus on the past 7 days. This is a news product, not a research report.

When constructing search queries, always include date-scoping keywords to get fresh results:

  • Use "this week", "today", "yesterday", or the specific date range (e.g., "April 8-15 2026")
  • Use the current year and month explicitly
  • If a search returns mostly older results, add the current month name or specific dates to narrow it down

Older context (e.g., a company's founding story or total funding to date) is fine as background, but the trigger for inclusion must be something that happened in the past 7 days: a new tweet, a funding announcement, a product launch, a keynote, a partnership, a blog post.

Scheduling Support

This skill supports scheduled execution. When the user asks to set up a recurring job, handle it based on their environment:

Claude Code — Session-scoped (CronCreate): If the user says something like "每天早上8点推送" or "set up a daily digest at 8am", and they're running in Claude Code:

Use the CronCreate tool with:

  • cron: an appropriate expression that avoids the :00 mark (e.g., "3 8 * * *" for ~8am daily, nudge a few minutes off the round hour to avoid API pile-ups)
  • prompt: "运行 agentic-commerce-news skill,搜索过去一周 agentic commerce 领域的最新动态,生成简报"
  • recurring: true

Tell the user:

  • Scheduled jobs live in the current Claude session memory (not persisted to disk by default — pass durable: true if they want it to survive restarts)
  • Recurring tasks auto-expire after 7 days of this session
  • Jobs only fire while the REPL is idle

Claude Code — Persistent (remote triggers): If the user wants a schedule that runs even when their laptop is closed, suggest they use the /schedule skill to create a remote trigger (managed by claude.ai). This runs on Anthropic's infrastructure, not locally.

OpenClaw: If the environment has openclaw CLI available (check with which openclaw), use openclaw cron add instead. OpenClaw jobs run 24/7 as a persistent agent.

Other runtimes: If none of the above is available, fall back to system crontab with a script that invokes the CLI (advanced).

Execution Flow

Phase 1: Broad Search (parallel, 8-12 queries)

Launch WebSearch queries in parallel. Every query must be scoped to recent content. Adapt the date references to the current date:

Breaking news & announcements:

  • "agentic commerce" news this week {current_month} {current_year}
  • "agentic commerce" startup launch OR funding OR announced {current_month} {current_year}

VC & Investment (this week):

  • agentic commerce startup funding raised {current_month} {current_year}
  • YC OR a16z OR Sequoia "agentic commerce" OR "AI shopping" investment {current_year}

Influencer activity (this week):

  • agentic commerce tweet site:x.com {current_month} {current_year}
  • "agentic commerce" OR "AI shopping agent" CEO founder opinion {current_month} {current_year}

Product launches & updates:

  • agentic commerce product launch update new feature {current_month} {current_year}
  • AI shopping agent checkout new product {current_month} {current_year}

Protocol & platform moves:

  • Shopify OR OpenAI OR Google agentic commerce update {current_month} {current_year}
  • Visa OR Mastercard OR Stripe agentic commerce news {current_month} {current_year}

Vertical signals:

  • agentic checkout payment startup news {current_month} {current_year}
  • brand AI agent storefront discovery news {current_month} {current_year}

Phase 2: Verify recency & fill gaps

From Phase 1 results, filter strictly:

  • Keep only items with activity in the past 7 days
  • Drop anything that's just a rehash of old news
  • For promising leads, do a quick targeted search to confirm details (funding amount, investor names, product specifics)

Phase 3: Classify into the Agentic Commerce Stack

Organize qualifying items into layers:

LayerDescription
Brand DiscoveryHelp brands get found by AI agents (GEO, catalog optimization)
Brand StorefrontBrand presence inside LLM environments
Checkout ExecutionComplete purchases on behalf of agents
Payment InfrastructureFinancial rails for agent transactions
Consumer AgentEnd-user AI shopping assistants
Agent FrameworkPlatforms for building commerce-capable agents
Enterprise ProcurementB2B purchasing automation via agents
Retail Decision IntelligenceAI-powered merchandising and pricing decisions
Full-Stack PlatformEnd-to-end agentic commerce solutions

Phase 4: Generate the weekly briefing

Structure the output as a news briefing:

Header:

## Agentic Commerce 周报({date_range})
> 本周 {N} 条值得关注的动态

For each item, use this card format:

### ProductName(事件类型:融资/产品发布/大V推荐/合作/观点)— 一句话摘要

**时间:** 具体日期
**背书:** 谁说的/谁投的/谁合作的

**核心内容:**
- 要点 1
- 要点 2
- 要点 3

**所属层级:** xxx

原文链接:https://...

Group cards by event type (融资动态 → 产品发布 → 大V观点 → 合作与生态 → 行业报告), not by layer.

Phase 5: Summary table

| 日期 | 公司/人物 | 事件类型 | 一句话摘要 | 层级 |
|------|----------|----------|-----------|------|
| 4/12 | Wildcard | 产品发布 | 推出 ChatGPT Shopping 优化工具 v2 | 品牌发现 |
| ... | ... | ... | ... | ... |

Phase 6: Weekly trend takeaways

Close with 3-5 short observations:

  • This week's biggest signal
  • Money flow direction
  • What big players are doing
  • Emerging themes vs. last week
  • One thing to watch next week

Quality Gates

  • Recency is the #1 filter. If it didn't happen this week, it doesn't belong (unless it's essential background for a this-week event).
  • Credible endorsement required. Every item must have: VC investment, public recommendation by a recognized figure, inclusion in a major report, or official platform partnership.
  • Source links are mandatory. No link, no inclusion.
  • Minimum 5 items. If it's a quiet week, 5 is OK. If you can't find 5, say so honestly rather than padding with old news.
  • No pay-to-play. Exclude items that only appear in sponsored content.

Language

Match the user's language. If the user writes in Chinese, output in Chinese (product names and proper nouns stay in English). If English, output in English. Default to Chinese with English proper nouns.

When the user asks for a specific vertical

Focus searches and output on that vertical only. Skip the full taxonomy.

When the user asks to go deeper on a specific item

Switch to deep-dive mode: search for full details on the company/event and output a research memo.

平台分布

OpenClaw

79.56%
按下载量换算780

安全审计

VirusTotal

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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