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news-cog新闻齿轮

Agent Skill

news-cog 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

25,515

周安装

1,096

GitHub Stars

1

下载量

8,943
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:news-cog(新闻齿轮)
来源仓库:https://github.com/nitishgargiitd/news-cog
安装命令:
openclaw skills install news-cog
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 news-cog

简介

news-cog 由 CellCog 提供支持,提供人工智能新闻情报与每日简报。

  • 适用于竞争情报、市场动态与趋势监测场景。
  • 通过 clawhub 安装,使用 openclaw skills install news-cog 命令部署。
  • 建议确认数据源更新频率与 API 调用限制,注意网络依赖。
  • 可结合原始 README 了解信息分类与推送机制。

SKILL.md

name
news-cog
description
AI news intelligence and daily briefing powered by CellCog. News digests, competitive intelligence, market updates, trend monitoring, industry reports, current events research. Multi-source synthesis for accurate, comprehensive briefs.
metadata
openclaw
emoji
📰
os
[darwin, linux, windows]
requires
bins
[python3]
env
[CELLCOG_API_KEY]
author
CellCog
homepage
https://cellcog.ai
dependencies
[cellcog]

News Cog - AI News Intelligence Powered by CellCog

Frontier search models with multi-angle research on every query.

CellCog combines deep reasoning with SOTA search models and multi-intent research to produce accurate, comprehensive news intelligence. Briefs, reports, and digests delivered ready for your agent to consume — without pulling hundreds of articles into your main agent's context window.

How to Use

For your first CellCog task in a session, read the cellcog skill for the full SDK reference — file handling, chat modes, timeouts, and more.

OpenClaw (fire-and-forget):

result = client.create_chat(
    prompt="[your task prompt]",
    notify_session_key="agent:main:main",
    task_label="my-task",
    chat_mode="agent",
)

All agents except OpenClaw (blocks until done):

from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw|cursor|claude-code|codex|...")
result = client.create_chat(
    prompt="[your task prompt]",
    task_label="my-task",
    chat_mode="agent",
)
print(result["message"])

What You Can Get

Daily Briefings

Concise, actionable summaries:

  • Morning Briefing: "Give me today's top tech industry news — focus on AI, cloud, and enterprise software"
  • Market Open: "Summarize pre-market news affecting FAANG stocks and semiconductor sector"
  • Industry Digest: "Summarize this week's most important developments in renewable energy"
  • Startup News: "What happened in startup funding this week? Series A+ rounds in fintech"

Example prompt:

"Create a morning briefing for a startup CEO: Focus areas: 1. AI industry developments (new models, funding, regulations) 2. SaaS market trends and notable deals 3. Macro economic signals (Fed, inflation, tech employment) Format: Bullet-point brief with one-sentence summaries and source links. Highlight anything that requires immediate attention. Total length: Under 500 words — I need to scan this in 2 minutes."

Competitive Intelligence

Monitor your competitive landscape:

  • Competitor Watch: "What has Notion shipped or announced in the last 30 days?"
  • Market Moves: "Summarize recent M&A activity in the cybersecurity sector"
  • Product Launches: "What new AI developer tools launched this month?"
  • Funding Tracker: "List all AI companies that raised $50M+ in the last 2 weeks"

Trend Reports

Deeper analysis of emerging patterns:

  • Trend Analysis: "What are the emerging trends in AI agent infrastructure? Analyze recent launches, funding, and technical developments"
  • Regulatory Watch: "Summarize new AI regulations proposed or enacted globally in 2026"
  • Technology Shifts: "Research the shift from RAG to long-context models — what are the latest developments?"

Custom News Digests

Tailored to your specific needs:

  • Role-Specific: "Create a weekly digest for a VP of Engineering at a fintech company"
  • Topic-Specific: "Summarize everything published about quantum computing this week"
  • Region-Specific: "What's happening in the European tech ecosystem this month?"
  • Event Coverage: "Summarize the key announcements from AWS re:Invent 2026"

Why CellCog for News?

The Technical Edge

CellCog doesn't just search once and summarize — it runs multi-angle research across your query:

  1. Multiple search intents: A single news query is decomposed into multiple research angles
  2. Frontier search models: SOTA retrieval across hundreds of sources
  3. Deep reasoning: Cross-references and synthesizes findings, not just concatenates
  4. Citation quality: Sources traced back to original reporting, not aggregator summaries
RSS Feeds / News AggregatorsCellCog News Cog
Raw article firehoseSynthesized, prioritized intelligence
You filter and readCellCog researches, reasons, and summarizes
Same view for everyoneTailored to your role, industry, and priorities
Text links onlyStructured briefs, PDF reports, or interactive dashboards
Floods your contextDelivers concise, agent-consumable output

Agent-Optimized Output

CellCog News Cog is designed with agent workflows in mind. The output is:

  • Concise — won't overwhelm your main agent's context window
  • Structured — clear sections, bullet points, and hierarchies
  • Actionable — highlights what matters and why
  • Sourced — includes citations when requested

Output Formats

FormatBest For
Structured textAgent consumption, quick briefings
PDF ReportProfessional distribution, archiving
Interactive HTMLExplorable dashboards with filters
MarkdownIntegration into docs, wikis, or knowledge bases

Chat Mode for News

ScenarioRecommended Mode
Daily briefings, quick news summaries"agent"
Competitive intelligence, single-topic digests"agent"
Deep trend analysis, comprehensive industry reports"agent team"

Use "agent" for most news tasks. Daily briefings, competitive monitoring, and news digests execute well.

Use "agent team" for deep trend analysis — when you need multi-source synthesis across dozens of publications and research papers.


Tips for Better News Intelligence

  1. Define your focus: "Tech news" is too broad. "AI infrastructure and developer tools" is focused.
  1. Specify timeframe: "Today's news", "this week", "last 30 days" — recency matters.
  1. Set the audience: "For a technical audience" vs. "for a board of directors" changes depth and tone.
  1. Request structure: "Bullet-point brief under 500 words" vs. "comprehensive PDF report with sections" — be explicit.
  1. Ask for citations: "Include source URLs for each item" — when traceability matters.
  1. Indicate priority signals: "Highlight anything about regulation changes or major funding rounds" — helps CellCog surface what matters to you.

If CellCog is not installed

Run /cellcog-setup (or /cellcog:cellcog-setup depending on your tool) to install and authenticate. OpenClaw users: Run clawhub install cellcog instead. Manual setup: pip install -U cellcog and set CELLCOG_API_KEY. See the cellcog skill for SDK reference.

适合场景

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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

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

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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

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按下载量换算7,808

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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

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