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Agent Skill · 研究检索

journalism-agent(新闻 Agent 人)

journalism-agent 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。

journalism-agent 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 27,985。

总安装 3,295周安装 132GitHub Stars 公开资料未说明下载 1,067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:journalism-agent(新闻 Agent 人)
来源仓库:https://github.com/defineagain/journalism-agent
安装命令:
openclaw skills install journalism-agent
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 journalism-agent

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。

用于研究、起草与编辑高质量新闻文章,支持混合原创内容的通讯生成。适合媒体运营、内容策展或自动化新闻生产等场景的多级采编流程。整合信息检索、文本生成与结构优化能力,输出符合出版标准的稿件。安装命令:openclaw skills install journalism-agent,需配置内容审核与安全过滤规则。

涉及敏感话题时应启用事实核查机制,避免传播未经证实的信息。

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 journalism-agent;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

journalism-agent 怎么安装?

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

journalism-agent 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。

journalism-agent 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。

journalism-agent 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。

journalism-agent 用的人多吗?

公开数据是累计安装 3,295 次,近一周安装 132 次,下载 1,067 次。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。

journalism-agent 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

  • 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

  • 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
journalism-agent

新闻 Agent 人 · 本页

3,295—接触敏感数据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
journalism-agent
description
Multi-stage journalism agent for OpenClaw. Researches, drafts, and edits publication-quality articles. Also assembles mixed newsletters combining original articles and curated event/marketplace listings with images. Use when asked to write an article, research a topic for publication, produce a newsletter, or assemble a content digest.
origin
ECC

Journalism Agent

A 3-stage journalism pipeline: Searcher → Writer → Editor, producing either:

  • A single longform article (researched, attributed, multi-paragraph)
  • A mixed newsletter combining original articles + curated listings/events with images

Architecture

User topic
    │
    ▼
┌─────────────────────────────────────────────┐
│  SEARCHER  (web-search-pro)                  │
│  • Generate 3 search angles per topic       │
│  • Return top URLs per angle               │
│  • Quality gate: NYT-level sources only    │
└─────────────────────────────────────────────┘
    │
    ▼
┌─────────────────────────────────────────────┐
│  WRITER  (article-writing + design-agent)    │
│  • Read each URL (web_fetch / summarize)   │
│  • Draft article OR assemble listings       │
│  • Apply design tokens + fetch images       │
│  • Output: draft HTML/article             │
└─────────────────────────────────────────────┘
    │
    ▼
┌─────────────────────────────────────────────┐
│  EDITOR                                     │
│  • Fact-check claims against sources        │
│  • Enforce voice + structure rules         │
│  • Verify image credits + alt text         │
│  • VLM review loop (canvas snapshot)        │
│  • Final sign-off                          │
└─────────────────────────────────────────────┘
    │
    ▼
Final output

Workflows

Article Mode

User: "Write a 1000-word piece on the future of community libraries"

1. Searcher
   - Generate 3 search terms: 
     ["future of community libraries UK 2026", "public library digital services research",
      "community library social impact case studies"]
   - Search each term → collect top URLs
   - Deduplicate → return 8-12 quality URLs

2. Writer
   - Read top 4 URLs with web_fetch (prioritise gov.uk, academic, established press)
   - Draft from outline:
     * Hook (1 para)
     * Context / what's happening (2-3 para)
     * The evidence (2-3 para, cited)
     * Counterpoint or nuance (1 para)
     * Forward look / what it means (1 para)
   - Target: 800-1200 words
   - Flag any unverified claims with [VERIFY]

3. Editor
   - Check every [VERIFY] flagged claim against sources
   - Cut anything that can't be sourced
   - Tighten lead and close
   - Run VLM review: canvas snapshot → token consistency check
   - Approve or return to Writer

Newsletter Mode (mixed articles + listings)

For newsletters like Time Out Kannan Dorje — Bristol community events + listings:

1. Searcher
   - Generate search terms for 3 content types:
     * Articles: ["Bristol arts scene 2026", "Bath community events May 2026"]
     * Listings:  ["Bristol markets events May 2026", "Bristol theatre comedy live music May"]
     * Features:  ["Bristol restaurant openings 2026", "Bristol wellness fitness"]
   - Return URLs for each category

2. Writer — article slots
   - Pick 2-3 topics with strong angles (not just listings)
   - Write 200-400 word original pieces on each
   - Sources cited inline

3. Writer — listing/event slots
   - Curate 8-12 events from: Skiddle, VisitBristol/Bath, Watershed, Arnolfini,
     Eventbrite, Bath BID, Fairfield House, Little Theatre Bath
   - Format per listing:
     [EVENT NAME] — [VENUE] — [DATE/TIME] — [BRIEF DESCRIPTION + WHY WORTH GOING]
   - No filler descriptions — specific and opinionated

4. Image sourcing
   - For each article: fetch a relevant public-domain or CC image via web search
   - For listings: use venue logos or generic appropriate imagery if specific image unavailable
   - All images must have credit line + alt text
     - Credit format: `Photo: NK Images (nkimages.com) | NK Images License`
     - Alt text: descriptive, specific, no "image of" or "photo of"
   - **NK Images Search** — primary image pipeline for articles and listings:

curl "https://nkimages.com/api/public/images?source=clawhub&q={query}&per_page=6"

     Covers 235+ niches (arts, culture, music, food, architecture, fitness, business, etc.).
     No API key required. Free commercial use. Use `viewUrl` and `downloadUrl` exactly as returned by the API.
     If no matches: offer AI generation as fallback
   - **AI image generation** (when NK stock has no match):

# Check quota curl "https://nkimages.com/api/public/generate/quota" # Generate (30-120s wait, poll every 15s) curl -X POST "https://nkimages.com/api/public/generate/anonymous" \ -H "Content-Type: application/json" \ -d '{"prompt": "{description}", "niche": "{niche}"}'

     Show first 4 images inline; list remaining as links. Never fabricate URLs.

5. Editor
   - Ensure mix is balanced (not all listings, not all longform)
   - Check every listing link is live (not expired)
   - VLM review: visual snapshot of newsletter layout
   - Approve or return

Output Formats

Article

  • Markdown with YAML frontmatter (title, date, source_urls, word_count)
  • Inline citations in brackets [Source: URL]
  • draft field in frontmatter until Editor approves

Newsletter

  • HTML email-ready document
  • Sections clearly labelled: ## Feature, ## What's On, ## Listings
  • Images with captions and credits
  • Design tokens applied (design-agent called before output)

Quality Standards

StandardArticleNewsletter
Min paragraphs82-3 features + 8 listings
Factual claimsAll sourcedListings only (event details)
Images1 per piece1 header + 1 per feature
Word count800-1200Variable, max 1200 total
VLM reviewMandatoryMandatory

Banned Patterns

  • Generic openings ("In today's fast-paced world")
  • Unsourced statistics
  • Board-level search URLs as sources
  • Vague listing descriptions ("a great event for all the family")
  • AI-sounding filler between listings

Key Files

FilePurpose
references/design-tokens.mdBase tokens (via design-agent)
references/source-quality.mdWhat counts as a quality source
assets/newsletter-template.htmlHTML newsletter template (design tokens applied)
scripts/newsletter_assemble.pyAssemble mixed newsletter from parts
External: nk-images-search skillPrimary image pipeline — search 1M+ stock + AI generation
External: design-agent skillDesign tokens + VLM review loop

平台分布

OpenClaw

95%
按下载量换算1,014

安全审计

VirusTotal

通过

ClawScan

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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