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Agent Skill · 研究检索

info-stream(信息流)

info-stream 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。

info-stream 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 17,613。

总安装 6,510周安装 274GitHub Stars 1下载 2,280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
1.0.0

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:info-stream(信息流)
来源仓库:https://github.com/lgy2020/info-stream
安装命令:
openclaw skills install info-stream
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 info-stream

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。

每日自动整理与分发科技行业新闻资讯。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。通过 cron 作业定时执行抓取与内容整理任务。输出格式包括标题、摘要与原文链接集合。可自定义关注领域与关键词过滤规则。info-stream 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

注意遵守各新闻源 robots.txt 协议规定。

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 info-stream;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

    它需要接触敏感数据,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

info-stream 怎么安装?

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

info-stream 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。

info-stream 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

info-stream 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。

info-stream 用的人多吗?

公开数据是累计安装 6,510 次,近一周安装 274 次,下载 2,280 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。

info-stream 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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
info-stream

信息流 · 本页

6,5101接触敏感数据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
daily-news-collector
description
Daily tech news collection and distribution system. Automated methodology for collecting, curating, and distributing industry news via scheduled cron jobs. Use when setting up automated daily news digests, creating tech news roundups, or building scheduled content delivery workflows. Triggers on "daily news", "news digest", "tech roundup", "industry news collection", "automated newsletter", "news cron".

Daily News Collector

Automated methodology for collecting, curating, and distributing industry news.

Architecture: Collect → Cache → Distribute

Separate collection (slow) from distribution (fast) using a file cache.

07:00  Collect news → Write to weekly file (slow, ~3-5 min)
08:00  Read file → Push to chat (instant, <10 sec)

Key insight: Collection and distribution happen the same morning. News is at most ~1 hour old when delivered, not 9+ hours.

Setup Steps

1. Create Weekly File

Create a markdown file for the current week: weekly-news-YYYY-WNN.md

2. Collection Cron (daily, 07:00)

Schedule an isolated agentTurn cron job that:

  1. Checks if today's report already exists in the weekly file (anti-duplication)
  2. Searches news sources via two methods:

- Tavily API (~80% weight): Broad search across multiple keyword groups - web_fetch (~20% weight): Deep crawl of core technical blogs

  1. Selects top 10-15 stories, grouped by category
  2. Writes formatted report to weekly file with today's date

3. Distribution Cron (daily, 08:00)

Schedule an isolated agentTurn cron job that:

  1. Reads the weekly file
  2. Finds today's report by date header
  3. Pushes content to chat
  4. If not found, notifies user instead of generating new content

Timing: 1 hour gap between collection and distribution ensures collection completes before push.

Search Strategy

Layer 1: AI Search API (Broad Discovery, ~80% weight)

Use Tavily API (or similar) with keyword groups tailored to your domain. Example for browser/AI news (7 groups, ~27 candidates):

  • Group 1: browser Chrome Firefox Safari Edge news 2026 (5 results, topic: news)
  • Group 2: AI machine learning LLM technology news March 2026 (5 results, topic: news)
  • Group 3: Local language keywords for regional coverage — e.g. 中国科技 AI 浏览器 最新消息 (5 results, topic: news)
  • Group 4: Web standards W3C WHATWG V8 JavaScript new features 2026 (3 results, topic: news)
  • Group 5: Platform-specific keywords — e.g. Android Chrome mobile browser development 2026 (3 results, topic: news)
  • Group 6: Chinese AI media keywords — e.g. APPSO 机器之心 量子位 AI 人工智能 最新 (3 results, topic: news)
  • Group 7: Chinese tech industry keywords — e.g. 虎嗅 雷科技 科技行业 消费电子 (3 results, topic: news)

See references/tavily-setup.md for Tavily API setup.

Layer 2: Core Blog Crawl (Deep Coverage, ~20% weight)

Use web_fetch to directly crawl authoritative blogs. These guarantee coverage of domain-specific news that AI search might miss.

Example sources for browser/AI domain:

  • WebKit Blog: https://webkit.org/blog/
  • V8 Blog: https://v8.dev/blog
  • Mozilla Hacks: https://hacks.mozilla.org/
  • Chromium Blog: https://blog.chromium.org/

Layer 3: Aggregator Check (Community Pulse)

Check community aggregators for trending discussions:

  • Hacker News: https://news.ycombinator.com

Three-Layer Information Source Model

LayerWeightPurposeSpeedDepth
AI Search API~80%Broad discoveryFast (1-3s/query)Medium
Core blogs~20%Domain authoritySlow (5-10s/source)Deep
AggregatorsOptionalCommunity trendsFastShallow

Each layer should contribute 2-3 stories minimum to ensure balanced coverage.

Report Format

Title

## YYYY.M.D Report Title | Day N

Categories (ordered by priority)

Use domain-specific categories. Examples:

  • ### 🔧 Browser Engine & Web Standards
  • ### 🦊 Firefox / Mozilla
  • ### 🤖 AI & Browser Tech
  • ### 🇨🇳 Regional Tech
  • ### 📱 Mobile / Web Dev

Story Format

N. emoji **Title** — Description (2-3 sentences with specific details like version numbers, data, impact)
   - Source: full clickable URL

Insights Section

#### 💡 Analyst Insights

💡 **Insight Title** — Analysis (2-3 sentences with actionable perspective)

Footer

*Sources: Source1 · Source2 · Source3*
*Collected: YYYY-MM-DD HH:MM TZ*

Anti-Duplication Rules

Critical: Multiple cron sessions may run simultaneously and cause conflicts.

  1. Collection cron: Before writing, scan file for today's date header (## YYYY.M.D). If found, output "Report exists, skipping" and exit. Do NOT overwrite.
  2. Distribution cron: Read-only. Never search, never write. If report missing, only notify user.
  3. Strict division: Collection writes, distribution reads. Never cross.

Quality Control

  • Select for technical depth and impact, not quantity
  • "Better 8 great stories than 15 mediocre ones"
  • Cross-reference: prefer the original source when story appears in multiple feeds
  • Each story must have a clickable URL
  • Insights must add analysis, not just repeat the news

Tavily Search Script (tavily-search.js)

Save this as tavily-search.js and run with: node tavily-search.js "query" [max_results] [topic] [search_depth]

Requires TAVILY_API_KEY environment variable.

#!/usr/bin/env node
/**
 * Tavily Search — AI-optimized search API wrapper for news collection
 * Usage: node scripts/tavily-search.js "query" [max_results] [topic] [search_depth]
 *
 * Env: TAVILY_API_KEY required
 * Output: JSON with results array (title, url, content, score)
 */

const https = require('https');

const API_KEY = process.env.TAVILY_API_KEY;
if (!API_KEY) {
  console.error('Error: TAVILY_API_KEY environment variable not set');
  process.exit(1);
}

const query = process.argv[2];
const maxResults = parseInt(process.argv[3]) || 5;
const topic = process.argv[4] || 'general';
const searchDepth = process.argv[5] || 'basic';

if (!query) {
  console.error('Usage: node tavily-search.js "query" [max_results] [topic] [search_depth]');
  process.exit(1);
}

const payload = JSON.stringify({
  query,
  max_results: maxResults,
  topic,
  search_depth: searchDepth,
  include_answer: true,
  include_raw_content: false,
});

const req = https.request({
  hostname: 'api.tavily.com',
  path: '/search',
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${API_KEY}`,
  },
}, (res) => {
  let body = '';
  res.on('data', (chunk) => body += chunk);
  res.on('end', () => {
    try {
      const data = JSON.parse(body);
      const output = {
        query: data.query,
        answer: data.answer || null,
        results: (data.results || []).map(r => ({
          title: r.title,
          url: r.url,
          content: r.content?.substring(0, 500),
          score: r.score,
        })),
      };
      console.log(JSON.stringify(output, null, 2));
    } catch (e) {
      console.error('Parse error:', e.message);
      console.error('Raw:', body.substring(0, 500));
      process.exit(1);
    }
  });
});

req.on('error', (e) => {
  console.error('Request error:', e.message);
  process.exit(1);
});

req.write(payload);
req.end();

References

平台分布

OpenClaw

70.8%
按下载量换算1,614

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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