Llm Wiki Newsroom
Self-evolving multi-agent "newsroom" that turns your documents into a cross-linked knowledge wiki — writer ≠ reviewer, local-first, no API keys, a structured alternative to RAG.
供给资产档案
研究与知识工作
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
场景
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
适配 Agent
Claude Code + Browser agents + CLI
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add alfadur7/llm-wiki-newsroom
维护状态
新鲜
距上次推送 8 天
风险
需审查
Permission surface may require sandboxing
GitHub 质量
77
77/100 质量 · 78/100 信任
覆盖标签
审查说明
Permission surface may require sandboxing · Quality score needs review
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
强可靠的选择,值得加入生产工作流候选列表。
信任
仅限沙盒有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
Stars
77 个 GitHub Stars
仓库活跃度
77 个 Star,14 个 Fork
维护状态
距上次推送 8 天
许可证
MIT
安装
npx skills add alfadur7/llm-wiki-newsroom
安装安全性
标准软件包或运行时安装路径
权限范围
shell or command execution, filesystem or document access
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 77 GitHub stars
- Stars/forks activity: 77 stars, 14 forks; issue activity unavailable in current metadata
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- RAG and knowledge 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Chunk documents
适用 Agent
安装决策
- 命令
- npx skills add alfadur7/llm-wiki-newsroom
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 70/100
- 审计
- 84/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- 没有内部安全审查的高合规环境
- 当前元数据中未发现重大风险信号
- 高风险权限提示:Shell 或命令执行
- Permission surface may require sandboxing
替代 Skill
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
替代 Skill
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
替代 Skill
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
替代 Skill
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent 安全 v2
52/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
- 高风险权限提示:Shell 或命令执行
- Permission surface may require sandboxing
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install alfadur7-llm-wiki-newsroomAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20Llm%20Wiki%20Newsroom%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20Llm%20Wiki%20Newsroom%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/alfadur7-llm-wiki-newsroom/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use Llm Wiki Newsroom in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Llm%20Wiki%20Newsroom%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/alfadur7-llm-wiki-newsroom/install
Install command: npx skills add alfadur7/llm-wiki-newsroom
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/alfadur7-llm-wiki-newsroom/install
LLM 文本格式
/api/skills/alfadur7-llm-wiki-newsroom/install?format=text
寻找替代方案
/api/skills/search?q=Llm%20Wiki%20Newsroom&limit=3
Agent 提示词
Use Llm Wiki Newsroom for this task. Review https://www.openagentskill.com/api/skills/alfadur7-llm-wiki-newsroom/install, then install with: npx skills add alfadur7/llm-wiki-newsroomRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Manifest
/api/registry/manifest/alfadur7-llm-wiki-newsroom
LLM 文本
/api/registry/manifest/alfadur7-llm-wiki-newsroom?format=text
安装别名
/api/registry/install/alfadur7-llm-wiki-newsroom
推荐
/api/registry/recommend?task=Use%20Llm%20Wiki%20Newsroom%20in%20an%20agent%20workflow&limit=3
适配 Agent
RAG and knowledge
平台
Python, Claude Code, Browser agents
Agent 决策面板
Companion skill for RAG and knowledge
将此 Skill 加入候选列表,并在生产使用前与相近替代方案比较。
栈中角色
辅助 Skill
主要匹配
RAG and knowledge
信任标签
强候选
安装路径
命令已就绪
适用场景
- RAG and knowledge 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 77/100 质量档案
- 6 个 OpenAgentSkill 交互事件
先审查
- 当前元数据中未发现重大风险信号
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次RAG and knowledge任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
仅限沙盒
有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
GitHub 采用度
检查77 个 GitHub Stars
Star/Fork 活跃度
检查77 个 Star,14 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过距上次推送 8 天
许可证清晰度
通过MIT
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 77 GitHub stars
- Stars/forks activity: 77 stars, 14 forks; issue activity unavailable in current metadata
- Permission surface: shell or command execution, filesystem or document access
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
质量档案
强 适用于 Agent 工作流的候选
可靠的选择,值得加入生产工作流候选列表。
工作流匹配
在这些场景使用此 Skill
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
工作流匹配
加入完整工作流
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
概览
# LLM Wiki Newsroom
[](LICENSE)
**A multi-agent AI knowledge base run by a five-role "newsroom" — open-source, local-first, no API keys, no vendor lock-in.** Drop articles, documents, and PDFs into the `raw/` folder, type a single command, and the newsroom — powered by an agent like Claude Code — reads them, extracts entities, concepts, and relationships, and organizes everything into a fully cross-referenced wiki, a structured and persistent alternative to RAG. Unlike most takes on the idea, the agent that *writes* a page is never the one that *reviews* it, and the authoring guidelines evolve themselves over time. Every new document you add also enriches the existing pages. This repo ships with a small example corpus — the debate over what "open source" means for AI — under `wiki/`, but the framework is domain-agnostic.
> Most knowledge tools leave the *finding* to you. This project **makes the AI read and understand** your collected documents first, then organizes them into a wiki — with cross-references between pages, automatic flagging of conflicting claims, and per-topic synthesis built in from the start, so later retrieval is fast.
> **See the output before installing** — the example corpus shipped in this repo is published as a browsable **[GitHub Wiki](https://github.com/alfadur7/llm-wiki-newsroom/wiki)** (no clone needed). It's a rendered static snapshot of the `wiki/` folder; the interactive graph below runs locally.

<sub>The interactive knowledge graph (`graph/graph.html`) — every page a node, every wikilink an edge, color-coded by auto-detected cluster, with a live physics layout and filter/search built in. Shown here on a larger private deployment (~2,300 nodes) to convey how it scales; **this repo ships a d
平台兼容性
技术详情
- 版本
- 1.0.0
- 许可证
- MIT
- 最近更新
- 2026年8月18日
- 发布时间
- 2026年7月22日
框架与工具
决策摘要
辅助 Skill
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 Llm Wiki Newsroom 准备的场景化草稿,可手动发布到 X。
A practical pick for design or creative work: Llm Wiki Newsroom: A multi-agent newsroom that transforms documents into a cross-linked wiki using local LLMs, designed for agent runtimes lik... 77 stars https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom?ref=x
可选:带安装命令的回复
Listing + install path for Llm Wiki Newsroom: https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom?ref=x Install: npx skills add alfadur7/llm-wiki-newsroom
收录来源
社区收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- alfadur7
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 社区收录 列表归属于 alfadur7,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom)
[](https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom)
[](https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom/audit)
[](https://www.openagentskill.com/skills/alfadur7-llm-wiki-newsroom)作者
alfadur7
@alfadur7
健康信号
- GitHub Stars
- 77
- 质量评分
- 48/100
- 最近 GitHub 推送
- 2026年8月14日
- 框架提示
- 1
- OpenAgentSkill 浏览量
- 6
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- GitHub 采用度77 个 GitHub Stars检查
- Star/Fork 活跃度77 个 Star,14 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护距上次推送 8 天通过
- 许可证清晰度MIT通过
- README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
- 依赖与运行时风险network or browser surface通过
相关 Skill
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
53.5K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
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